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Assessing the Disruptive Potential of Space Technology Concepts: Development and Application of an Evaluation Method
By Dimitrios Giannoulas
Assessing the Disruptive Potential of Space Technology Concepts: Development and Application of an Evaluation Method
Diploma Thesis
Assessor: Prof. Dr. Hans Georg Gemünden Co-Assessor: Dipl.-Ing. Aiko Karaschewitz School of Economics & Management Institute of Technology & Management
Supervisor: Egbert Jan van der Veen, MSc DLR Institute of Space Systems Department of System Analysis Space Segment Dimitrios Giannoulas Martr.Nr. 199380 Wörther Str. 33 10405 Berlin - Germany Tel: +49 30 38308105 [email protected] Berlin, May 23, 2012
Freie wissenschaftliche Arbeit zur Erlangung
des Grades eines Diplom-Ingenieurs
am
Institut für Technologie und Management
TIM – Lehrstuhl für Innovations- und Technologiemanagement
Prof. Dr. Hans Georg Gemünden
Fakultät VII (Wirtschaft und Management)
Technische Universität Berlin
Assessing the Disruptive Potential of Space Technology Concepts:
Development and Application of an Evaluation Method
Eingereicht von: Dimitrios Giannoulas Matrikelnummer: 199380 Studiengang: Wirtschaftsingenieurwesen Anschrift: Wörther Str. 33, 10405 Berlin Telefonnummer: +49 30 38308105 E-Mail: [email protected] Berlin, den 23. Mai 2012
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Abstract
ii
Abstract
Since the introduction of the term disruptive technologies by Bower and Christensen in
1995, a multitude of research has been performed on how these technologies create new
markets and provide more value for the customer in comparison to incremental or
sustaining innovations. However, little is known about what disruptive technologies for
the space sector are, the impact they can have on the space market and what benefits can
be attained through them.
The first objective of this thesis is to develop a systematic technology evaluation method
to support decision making in the evaluation of the disruptive potential of new
technologies and technology concepts in the space sector. The second objective is to
perform a practical application of the developed method and thereby validate it. This is
achieved by means of a case study conducted within the frame of a larger research project
on disruptive space technologies performed at the German Aerospace Center’s Institute of
Space Systems.
The developed method involves a combination of several technology evaluation
techniques. The Analytic Hierarchy Process is utilized as a pre-selection process and as a
method for determining the weights of the evaluation criteria. A Delphi method is used as
a detailed evaluation process for technology concepts with a high potential for
disruptiveness. For both techniques, Concept Scoring is implemented for the interpretation
of the results. The case study results show a ranking of the 20 most promising candidates
for disruption inside the technology domains power, data handling, materials and
propulsion. The case study also provides proof of concept for the developed method and
demonstrates its applicability and effectiveness.
Preface
iii
Preface
This work represents my diploma thesis and constitutes the conclusion of my studies in
engineering management at the Berlin Institute of Technology. It was written during the
course of seven months of research at the German Aerospace Center’s (DLR) Institute of
Space Systems in Bremen, Germany as part of a major project on disruptive space
technologies contracted by the European Space Agency and conducted at the DLR.
First and foremost, I would like to express my sincere gratitude to my supervisor and dear
colleague Mr. Egbert Jan van der Veen. His guidance, his inspiration and his insights
contributed to a large degree to this thesis and I really appreciate all the help he has given
me during my stay at the DLR – both on and off the subject. He sparked my enthusiasm
for disruptive (space) technologies and I will continue to advocate for them and research
on the subject for as long as I can.
I would also like to thank the participating experts of the Delphi survey who invested
many hours of their valuable time to complete the questionnaires. They did so without
having any obligation and without expecting anything in return. For that I am grateful.
Their participation and their expertise were crucial to the application of the evaluation
method, the outcome of the case study and possibly for the development of a future
disruptive technology in the space sector.
Last but not least, I would like to thank my parents for all of their support during the years
of my studies. This thesis and my upcoming diploma would not have been possible
without them.
Table of Content
iv
Table of Content
Abstract ............................................................................................................................... ii Preface ............................................................................................................................... iii Table of Content ................................................................................................................. iv List of Figures ....................................................................................................................... v List of Tables ....................................................................................................................... vi List of Acronyms and Abbreviations .................................................................................... vii
Introduction .............................................................................................................. 1 1 Rationale .............................................................................................................. 1 1.1 Research Objective ................................................................................................ 2 1.2 Conceptual Framework and Methodology ............................................................. 3 1.3 Research Layout .................................................................................................... 5 1.4
Theoretical Background ........................................................................................... 7 2 Basic Terminology ................................................................................................. 7 2.1 Technology Evaluation Methods .......................................................................... 12 2.2 Space Sector Analysis .......................................................................................... 14 2.3
DLR Study Findings ................................................................................................. 19 3 Disruptive Space Technologies ............................................................................. 19 3.1 Evaluation Method Analysis ................................................................................. 21 3.2 Search Strategy Development .............................................................................. 25 3.3
Research Methodology .......................................................................................... 27 4 Evaluation Method Selection ............................................................................... 27 4.1 Criteria Selection ................................................................................................. 32 4.2 Criteria Weighting and Scoring ............................................................................ 34 4.3
Presentation of the DST Evaluation Method ........................................................ 37 5 DST Evaluation Method ....................................................................................... 37 5.1 Criteria Selection ................................................................................................. 38 5.2 Weighing & Scoring ............................................................................................ 41 5.3
Case Study: Disruptive Technology Search for Space Applications ..................... 43 6 Research Objectives ............................................................................................ 43 6.1 Case Study Design .............................................................................................. 44 6.2 Presentation, Analysis and Interpretation of Results .............................................. 49 6.3
Conclusions ............................................................................................................. 53 7 Limitations of the Study ...................................................................................... 53 7.1 Implications for Future Research .......................................................................... 54 7.2 Recommendations .............................................................................................. 55 7.3
Bibliography ...................................................................................................................... viii Appendix 1 ....................................................................................................................... xiv Appendix 2 ....................................................................................................................... xvi
List of Figures
v
List of Figures
Figure 1. Research objectives of this work. ........................................................................... 3
Figure 2. Structure of DLR research. ..................................................................................... 5
Figure 3. The wheel of innovation. ....................................................................................... 9
Figure 4. Perceived performance mix of portable music players in the Discman era. ............. 10
Figure 5. Operating principle of evaluation methods. .......................................................... 12
Figure 6. ‘Five Views of the Future’ strategic analysis framework. ........................................ 14
Figure 7. Key players of the space industry. ........................................................................ 15
Figure 8. Example of the AHP process. ............................................................................... 28
Figure 9. Research objectives of the case study. .................................................................. 43
Figure 10. Distribution of expert survey respondents. ......................................................... 45
Figure 11. Formula for the calculation of the performance attribute weights. ...................... 47
Figure 12. Sample of the Delphi expert database. ............................................................... 48
List of Tables
vi
List of Tables
Table 1. Examples of disruptive technologies ...................................................................... 11
Table 2. Evaluation methods overview ............................................................................... 25
Table 3. Search methods overview ..................................................................................... 26
Table 4. Example of a concept scoring matrix .................................................................... 32
Table 5. The fundamental scale for pairwise comparisons ................................................... 35
Table 6. Pairwise comparison of the AHP criteria for the 4 domains of the STEP framework . 35
Table 7. Comparison matrix for priority calculations ........................................................... 35
Table 8. The basic technology readiness levels .................................................................... 45
Table 9. Delphi results ranked by category ......................................................................... 50
Table 10. Delphi results ranked by total score ..................................................................... 51
List of Acronyms and Abbreviations
vii
List of Acronyms and Abbreviations
Acronym Explanation
A1 Attribute 1
AHP Analytic Hierarchy Process
DLR Deutsches Zentrum für Luft- und Raumfahrt (German Aerospace Center)
DST Disruptive Space Technology
DSTs Disruptive Space Technologies
DT Disruptive Technology
DTs Disruptive Technologies
EQ Economic question
ESA European Space Agency
NASA National Aeronautics and Space Administration
SEP Social, Economic and Political
SMTs Scanning, Monitoring and Tracking techniques
SQ Social question
STEP Social, Technical, Economic and Political
TQ Technical question
TRL Technology Readiness Level
Introduction
1
Introduction 1
Every revolutionary idea seems to evoke three stages of reaction. They may be summed
up by the phrases:
(1) "It's completely impossible - don't waste my time";
(2) "It's possible, but it's not worth doing";
(3) "I said it was a good idea all along."
- Arthur C. Clarke (1985)
Rationale 1.1
One of the most prominent theories within business, innovation and technology
management literature deals with the disruption of dominant technologies and the
respective markets by new technologies or so called disruptive technologies (DTs). This
theory was first developed by Joseph L. Bower and Clayton M. Christensen (1995) and
describes how new technologies enter a market and disrupt the status quo of that market
by pushing the currently dominant technology along with its manufacturer out of the
market. Since then, this theory has received high attention from industry leaders because
of the great threat disruptive technologies pose to the incumbent technology leaders. The
importance of the notion of disruption has evoked a great deal of research on the subject
and a lot of literature has been written in the last two decades, most notably the work of
Christensen (1997; 2003), Adner (2002) and Evans (2002). More recently, however,
scholars have adopted the notion that the theory is not a-one-size-fits-all-theory and that
it has to be adapted to the unique market dynamics of different sectors. Examples of
these adaptions include:
• Education (Christensen, Horn, & Johnson, 2008)
• Medicine (Christensen, Grossman, & Hwang, 2009)
• Military (Mitchell, 2009)
• Gaming technology (Smith, 2007)
• Information technology (Peterson, Anderson, Culler, & Roscoe, 2003)
For the space sector, little to no research has been performed on how disruptive
technologies emerge, how the disruption occurs and what benefit can be potentially
attained through them.
The dynamics of the space sector are fundamentally different from the ones in classic
consumer-driven markets. Space technologies have a far slower pace of evolution and the
time span in which they emerge is often longer. The reason for this is that the space
Introduction
2
market is not defined by consumers and profit-driven businesses but rather by space
agencies and, in extension, the governments they represent. Also, the hostility of the
operating environment and the high cost associated with failure calls for materials and
components with proven reliability so that a certain probability of mission success can be
ensured. As a consequence, an inclination towards dependable and well-proven
components can be observed and the entry of innovative technologies in the market is
hampered. Currently, many space technologies only bear the potential for incremental
and sustaining innovation. In order to achieve these minor improvements in performance,
often a large number of resources are required.
Radical technologies, however, are key causal agents of disruption. Only new concepts,
out of-the-box thinking and breakthrough technologies have the chance to bring up new
momentum into space technology development. In this way, disruptive technologies
might facilitate to innovate the space market. Benefits like lighter materials, higher
performance levels and decreased production and integration costs are only some
examples for possible outcomes. Disruptive technologies can change the layout of the
space market and change the sector in a way that the present dominant technologies may
become obsolete. The importance of innovative concepts and the difficulty of finding and
implementing them are reflected not only by the introductory quote by Arthur C. Clarke
on Page 1. Also supporting this is a quote from the European Space Agency’s Technology
Readiness Levels Handbook for Space Application (2008) who state that:
The ability to make good decisions concerning the inclusion or exclusion of new
technologies and novel concepts, and to do so in the absence of perfect information, is
essential to success of many space programs. […] Numerous approaches have been
developed to assist in meeting this management challenge, including the use of a
variety of decision support tools. A critical step in all such methodologies, however, is
the consistent assessment […] of various advanced technologies prior to their
incorporation in new system development projects. (p. 1)
Research Objective 1.2
To date, there is no empirically tested evaluation method for assessing the disruptive
potential of space technology concepts. The first objective of this research is to develop a
systematic evaluation method that encompasses technology concepts from within the
space sector as well as technology concepts from other industry sectors that can
potentially be beneficial and work in a space related environment, so called spin-in
technologies. This evaluation method is a generic process that is applicable to all
technology domains of the space sector. The aim of the method is to provide decision
Introduction
3
makers with the necessary information needed for future technology development
decision by providing an indication of the disruptive potential of a technology concept.
The second objective is the application of the developed evaluation method. The aim of
the application is twofold. Firstly, it provides a ranking of the 20 currently available
technologies that have the highest potential for disruptiveness inside four major
technology domains of the space sector. Secondly, it serves as validation for the
theoretically developed method and explores weak spots of the method. A detailed
description of the application of the method and its aims is given in Section 6.1 of
Chapter 6.
The two research objectives of the thesis are depicted in Figure 1 along with the respective
aims of each objective.
Figure 1. Research objectives of this work.
Conceptual Framework and Methodology 1.3
This research is conducted in the context of a major research project involving disruptive
technologies in the space sector. The study with the title Disruptive Technology Search for
Space Application is performed at the German Aerospace Center’s (DLR) Institute of Space
Systems on behalf of the European Space Agency (ESA). It has the goal of identifying
technology concepts with a high potential for disruptiveness for the coming two decades
for the space sector in order to support decision making in ESA’s technology development
strategy. To reach this goal, the following sequent steps are performed in the context of
the DLR study:
1) Development of a theory on disruptive technologies for the space sector
2) Development of a search strategy and building of a database of technologies with
disruptive potential that serves as a basis for technology evaluation
3) Development of a technology evaluation method for technology concepts with
potential for disruptiveness
Introduction
4
4) Application of the evaluation method in order to identify technology concepts
with a high potential for disruptiveness
5) Formulation of a development plan for the identified technology concepts
This thesis is part of the DLR study and the scope is limited to the development of the
evaluation method and its application, as defined in the research objectives. However, the
development of the evaluation method cannot be regarded as an independent process.
The theory on disruptive technologies in the space sector is an essential part of the
development of the method since the method is based on the theory. Also, the
development of the search strategy and its application are essential to the application of
the evaluation method because the created database serves as a basis for the evaluation.
The steps of the DLR study and the interconnections between them are shown in Figure 2.
The red frame shows the parts of the DLR study that are object of this thesis.
The development of the evaluation method is based on the theory of disruptive
technologies for the space sector as devolved in an earlier stage of the DLR study and
depicted in Figure 2. This theory serves as background knowledge and influences the
method development process. Furthermore, the development of the method is done by
considering various technology evaluation methods and analyzing them according to
space sector specifics.
The application of the method is done in form of a case study. This research design is
chosen to document the practical application of the method in the context of the DLR
project as shown in Figure 2. The nature of the application is both descriptive and
exploratory, which are both valid for case studies (Yin, 1993).
Introduction
5
Figure 2. Structure of DLR research. The scope of this thesis is highlighted.
Research Layout 1.4
Chapter 1 serves as the introduction and gives an overview of what the rationale behind
the research is, what the research objectives are and illuminates the interconnections
between this research and the DLR study Disruptive Technology Search for Space
Application.
Chapter 2 represents a review of business literature and provides the theoretical
knowledge and the necessary information for the comprehension of the following
chapters, especially the work that has been done in the DLR study. In Chapter 3, the work
done in the DLR study is presented. Both these chapters serve as the theoretical
background for this thesis. The reason for dividing the theory into two chapters is to
emphasize the differences between theoretical knowledge that originated out of business
literature and is widely accepted and accessible and theoretical knowledge that is done
solely for the purpose of the research and is not yet public knowledge.
Introduction
6
In Chapter 4 the methodology of the evaluation method design is elaborated. Chapter 5
presents the method as a generic process and gives explanations of the main features. A
practical application of it in the frame of a case study is found in Chapter 6. Conclusions
of the study that include limitations and implications for future research are discussed in
Chapter 7. This chapter also gives recommendations for further steps that can follow the
evaluation process.
Appendix 1 and 2 show the results of the surveys conducted in the case study providing a
detailed example of a practical application of the evaluation method. The data also
substantiates the voting of the experts and gives insights on their choices. Especially the
comments given by the experts can be of great value for the potential future development
of the technologies.
Theoretical Background
7
Theoretical Background 2
This chapter represents a review of literature and serves as the theoretical background of
the study. It provides the reader with the necessary information for the comprehension of
the following chapters, especially the work that has been done in the DLR study Disruptive
Technology Search for Space Application and is elaborated on in Chapter 3.
The basic terminology of this study is defined in Section 2.1. The information given in this
section is imperative for the understanding of the study and the introduced terms are used
in almost all chapters. Section 2.2 represents a review of available methods for technology
evaluation already in use in technology forecasting. It explains key features of evaluation
methods in order to give a general overview of what they are and what they are trying to
accomplish. In Section 2.3 the space sector infrastructure is analyzed with respect to
technology development. It gives the reader an outline of what the space sector looks like
and what its main characteristics and major differences to other sectors are.
Basic Terminology 2.1
2.1.1 Technology
Nowadays, the word technology is often associated with complex machinery, consumer
electronics or software. However, the word “technología” (τεχνολογία) in ancient Greek
has a broader meaning. The word’s translation is twofold: “téchnē” (τέχνη), which is a
craft or an art, and “logía” (λογία), which means the knowledge of a discipline. Several
dictionaries provide different definitions for the word technology; however, they all focus
on the following central themes (cf. Oxford Dictionaries, 2011; Merriam-Webster, 2011):
• The practical application of knowledge (knowledge is often referred to as scientific
knowledge)
• Ways of making or doing things
• The sum of a society’s or a culture’s practical knowledge, especially with reference
to its material culture
• The use of tools, machines, materials, techniques, and sources of power to make
work easier and more productive
As can be seen, the meaning of the term technology is ambiguous and depends on the
purpose of the word for the user. Therefore, regarding the present activity, the following
working definition applies:
Theoretical Background
8
Technology is the practical application of scientific knowledge in creating tools, machines,
materials and techniques, enabling or increasing the efficiency of human activities.
2.1.2 Innovation
While technology is any practical application of knowledge, innovation is often seen as
doing something in a different way or as a successful exploration of new ideas. Innovation
is a word derived from the Latin word “innovare” and according to several experts like
Tidd, Bessant, and Pavitt (2005) or Ayres (1969) means: “to make something new”.
Therefore, this research uses the following working definition:
Innovation is the application of an idea or an invention that constitutes a change in the
existing order.
It is important to note, because of a common misconception, that innovation is
fundamentally different from invention. The typical distinction between an invention and
an innovation is that an invention is a manifested idea and innovation is a successfully
applied idea. Ergo, even the best invention has no economic value, if it cannot be turned
into an innovation. Supporting this is the following quote from Roberts (1987):
“Innovation = invention + exploitation”
According to Francis and Bessant (2005), innovations can be classified into four broad
categories called the 4Ps of innovation: Product innovation, process innovation, position
innovation and paradigm innovation. Tidd at al. (2005) give the following explanations for
each of the 4Ps:
• Product innovation: Improvement in a product or a service
• Process innovation: Improvement in the way a product/service is created and
delivered
• Position innovation: Improvement in the context, in which the product/service is
introduced
• Paradigm innovation: Improvement in the underlying metal model that frames
what an organization does
A second dimension to be considered is the degree of novelty involved, stretching from
incremental to radical innovation. Doing something, that you do, better constitutes an
incremental improvement (for example improving the performance of a car engine) while
introducing a new thing to the world (for example a fuel cell powered car engine) can be
considered a radical innovation (Tidd et al., 2005).
Theoretical Background
9
This study focuses only on radical product innovation. For a better understanding, Figure 3
illustrates how the 4Ps interact with the degree of novelty and shows the focus of this
research. Innovation can take place on an axis running through from incremental to
radical change; the area inside the circle maps the potential space of innovation (Tidd at
al., 2005).
Figure 3. The wheel of innovation. Adapted from Managing Innovation: Integrating Technological,
Market and Organizational Change (p. 13), by J. Tidd, J. Bessant, and K. Pavitt, 2005, Chichester:
John Wiley & Sons.
2.1.3 Perceived Performance Mix
Companies marketing technologies attempt to satisfy customer demands. However, the
demands and requirements for technology performance differ from customer to
customer. In marketing literature, this heterogeneity in customer demands is called
customer-perceived value (Yang & Peterson, 2004). The objective of this research is to
determine the performance of a technology not on a single attribute but rather on a
composition of different performance attributes like for example cost, speed, mass and
efficiency. Taking both factors into account, a new concept under the term perceived
performance mix is hereby introduced by the author. It represents a mixture of the
relevant performance attributes as perceived valuable by a customer or a part of the
market. This leads to the following definition:
The perceived performance mix is the mix of functional attributes of a technology as
appeared valuable to the customer.
To further illustrate this, the following example is given:
Product
Focus of currentresearch
Paradigm(mental model)
Process
Position
InnovationIncremental…radical Incremental…radical
Incr
emen
tal…
radi
cal
Incremental…
radical
Product
Focus of currentresearch
Paradigm(mental model)
Process
Position
InnovationIncremental…radicalIncremental…radical Incremental…radicalIncremental…radical
Incr
emen
tal…
radi
cal
Incr
emen
tal…
radi
cal
Incremental…
radicalIncrem
ental…radical
Theoretical Background
10
Although the Discman originally was a Sony brand trade name for its first portable CD
player introduced in 1984 (Sony Global - Press Release), it has become a generic
trademark generally used for all portable CD players. With the introduction of portable
mp3 players to the market in the late 1990s, the Discman market has undergone a
significant disruption (Beaudry, 2007). This disruption is primarily owed to the change of
how the customers value certain performance attributes. Figure 4 illustrates this change
with the help of a radar chart. The left image shows the performance attribute mix as it
was before the introduction of mp3 players. Sound quality was valued most by the
customers since this was the main advantage of the CD over the cassette. Additionally,
battery life and exchangeability of the medium were very important. With the introduction
of the mp3 format, however, this changed dramatically. With a certain level of sound
quality and rechargeable batteries taken for granted customers focused more on other
attributes like capacity and portability/size. This ultimately led to the decline of the
Discman demand.
This shift in the perceived value of a specific mix of attributes constitutes the shift in the
perceived performance mix. It is very important for understanding disruptive technologies,
as it is often the alternate performance mix that appeals to the customers and thus
making the technology disruptive and not one single performance attribute. This can be
seen very well in the example of the Discman: Despite the fact that the sound quality of
the CD is vastly superior to the mp3 (Meyer, 2000), people stopped valuing the
performance mix of the CD and turned to the performance mix provided by the mp3
format although inferior on some attributes.
Figure 4. Perceived performance mix of portable music players in the Discman era. Data comes
from personal experience with portable music players and is used to illustrate the concept of
perceived performance mix. It is not empirically ascertained.
Theoretical Background
11
2.1.4 Disruptive Technologies
A technology that emerges out of a niche market and becomes so dominant that it
disrupts the status quo of a market and often leads to incumbent companies being
pushed out of the market is called disruptive technology (DT) (Christensen, 1997). The
term was introduced in 1995 by Joseph L. Bower and Clayton M. Christensen. Disruptive
technologies (DTs) are since popular object of research (also see Paap & Katz, 2004;
Danneels, 2004; Sood & Tellis, 2005; Carayannopoulos, 2009) due to the threat that they
pose to established, market-leading companies. Table 1 shows a few examples of
disruptive technologies of the past 30 years.
Table 1
Examples of disruptive technologies
Dominant Technology (Incumbent)
Disruptive Technology (New entrant) Disruptive Attribute Period of
Disruption
Workstations Personal Computers Cheap, for everyone 1980’s
5.25 inch disk drive 3.5 inch disk drive Size, weight (laptops) 1980’s
Chemical Photography Digital Photography Capacity, development 2000’s
Compact Cassette Compact Disc Sound quality, capacity 1990’s
Discman Mp3 players Portability, capacity 2000 - 2005
Note. Data comes from various sources in magazines, books and online.
When a technology emerges, it is valued by the customers mainly on its most critical
performance value (Adner, 2002). Over time, however, when the initial basic functionality
or functional threshold is reached, the perceived performance mix of the technology starts
to change. Disruptive technologies start out as inferior products serving a market niche. As
technologies mature and the perceived performance mix changes, they start over-
performing the dominant technology and appealing to the mainstream market. When this
happens, the new technologies rapidly become the new standard and the old
technologies along with their producers are being pushed out of the market. Because of
the DTs’ initial technological inferiority and the differences in the perceived performance
mix, established companies are often blind-sighted against the potential of the new
technology. They believe that it can only serve a niche market and that the majority of
their customers will not value its use. In fact, it is often their customers themselves that tell
the incumbents that they do not value the new features (Christensen, 1997). Also
supporting this is a quote from Tellis (2006, p. 34): “[…] the disruption of incumbents - if
Theoretical Background
12
and when it occurs - is due not to technological innovation per se but rather to
incumbents’ lack of vision of the mass market and an unwillingness to cannibalize assets
to serve that market.”
From the above elaborated the following definition for DTs is derived:
A disruptive technology is a technology that disrupts the status quo of both the market
position of the dominant technology and the competitive market layout by having an
alternate perceived performance mix, which is valued more by the customer than the one
of the dominant technology.
Technology Evaluation Methods 2.2
Technology evaluation methods are used to justify decisions in technology investments.
After evaluating technologies on their potential for future success, a forecast can be
made. Because of this, forecasting methods are often used synonymously for technology
evaluation methods. Forecasting methods use information from the past to forecast
events in the future as depicted in Figure 5. This information can come in many forms like
for example experience, performance data, intuition, trends and patterns. This process is
based on the assumption that powerful feedback mechanisms in human society cause
repetitive processes (i.e. future trends and events to occur in identifiable cycles and
predictable patterns based on the past).
MethodsInformation Forecast
Past Present Future
Figure 5. Operating principle of evaluation methods.
Accurate evaluation methods can contribute to the selection of the best alternatives
leading to the best possible future state of the system. In here lays the forecasting
dilemma: selecting a technology for development is essentially a self-fulfilling prophecy as
it tries to measure if it gets developed in order to decide if it gets developed (Henshel,
1982). For example, a space technology that is identified as having a high potential of
becoming a DST will be invested in and in this way become disruptive. In light of this, the
term evaluation might be more appropriate because a technology concept will be
Theoretical Background
13
evaluated on what its possible future can be and how beneficial this will be to the actors
involved. Therefore, the term evaluation methods is used from now on.
Because of the clear benefit of evaluation, an extensive amount of literature has been
written on this subject. Within this literature, different approaches of creating views on
the future can be identified. In general, these views can be categorized as being either
quantitative, qualitative or a combination of both. These different approaches are
determined by separate sets of system thinking. System thinking is the process of trying to
understand how elements interact and influence each other within a whole. According to
Jackson (2000), there are two different ways of viewing systems: a hard systems approach
and a soft systems approach.
Hard system analysis relies on quantitative methods and involves mostly simulations and
mathematical techniques. The underlying view of this approach is that reality can be
quantified and analyzed on quantitative variables. The benefit of this approach is that it is
highly accurate. It can, however, take into account only simple elements and not complex
measurements like opinions, culture and politics.
Soft system analysis relies on qualitative methods and is used for complex systems that
cannot be easily quantified. It is especially useful for situations where complex human
factors define interactions and relationships.
Vanston and Vanston (2004) developed a framework for strategic analysis based on how
people see the future. These views are represented by five different kinds of people:
Extrapolators, pattern analysts, goal analysts, counter-punchers and intuitors. As illustrated
in Figure 6, these five views form different categories containing several methods of
evaluation. They are depicted on an axis going through from quantitative to qualitative
methods and are described and assessed on their advantages, disadvantages and
applicability as evaluation methods for space technologies in the DLR study “Disruptive
Technology Search for Space Application”. Here, they are summarized in Section 3.2 of
Chapter 3.
Theoretical Background
14
Figure 6. ‘Five Views of the Future’ strategic analysis framework. Adapted from “Testing the Tea
Leaves: Evaluating the Validity of Forecasts,” by J. H. Vanston and L. K. Vanston, 2004, Research-
Technology Management, Volume 47, Number 5, p. 36
Space Sector Analysis 2.3
This section presents an analysis of the space sector and a presentation of its
characteristic, its innovation dynamics and the different pathways of space technology
development within the sector.
2.3.1 Space Sector Infrastructure
The space sector is a complex market which is highly influenced by governmental entities.
Spread over the world, there are over 50 space agencies (for example NASA, ESA, JAXA
and Roskosmos), more than 40 commercial operators and several institutional entities (for
example NOAA, EUMETSAT, JME, and EC) that are procuring satellites and satellite related
services. The key players of the space sector can generally be divided into two types;
governmental institutions and commercial organizations (Tkatchova, 2011). These two
types and their different sub-types are illustrated in Figure 7.
Theoretical Background
15
Figure 7. Key players of the space industry. Reprinted from “Disruptive Space Technologies,” by E.
Veen, M. Gugliemi, D. A. Giannoulas, and D. Schubert, 2012, Manuscript submitted for
publication. Reprinted with permission.
Funding for technology research and development generally flows from governmental
institutions and network operators to the space sector industry. This funding has either
military or civilian purposes (although many forms of dual-use technology development
exist). Civilian missions can be categorized into commercial and scientific missions. For
military missions, governmental institutions are the sole customers. For the civil purposes -
both commercial and scientific missions - customers can either be governmental
institutions or end-users/industry.
In general, the following market forms can be identified:
• Mass market: Multiple sellers that face multiple buyers
• Monopoly market: One seller that faces multiple buyers
• Monopsony market: One buyer that faces multiple sellers
• Oligopoly market: Few sellers that face multiple buyers
• Oligopsony market: Few buyers that face multiple sellers
The space sector has been characterized as a monopsony market, in which the government
is the main investor in space related technologies (Szajnfarber & Weigel, 2007; Summerer
2011). This seems to hold up for civilian-science and military missions that rely mainly on
governmental funding but not for civilian-commercial missions. Within the
telecommunications and navigation market there are billions of potential customers, which
make an oligopoly a more suitable characterization for this part of the market.
Theoretical Background
16
2.3.2 Space Technology Requirements
Within the space sector, research and development and the diffusion of technologies
within their respective market are different when compared to terrestrial markets. Space is
an especially harsh environment, which is not only hard to reach but also hard for
technologies to operate in. This creates unique constraints in form of performance levels
that greatly exceed those required for terrestrial technologies. These performance levels are
determined by the following environmental constraints:
• High-energy radiation (both ionizing and electromagnetic)
• Extreme temperatures
• Large and frequent temperature variation
• Micrometeoroid and orbital debris impacts
• (Partial) vacuum
• High and low g-forces
• Limited opportunities for repairs or adjustments after launch
The constraints of the space environment have led to the following quality requirements
for space technologies:
• High testing requirements – the multitude of environmental conditions are adding
cost and complexity to the testing process
• High need of redundancy - in order to deal with unforeseen events and failures, a
high degree of redundancy is required
• Strict quality assurance and quality control processes – to ensure functioning of
technology under the right circumstances, strict quality control and assurance
processes are required
• Long flight heritage – for vital missions, only components and sub-systems that
have proven their capability to function in the actual space environment are chosen
Because of these high quality requirements, the following consequences for the market
dynamics of the space sector can be observed:
• Low production volumes: Most of the new technology development is done from a
mission pull perspective. This means that components are often designed to order.
(Note: there has been an increasing trend towards the use of commercially
available off the shelf (COTS) products in order to save costs).
• Reluctance to cannibalize: Space technologies often have a significant amount of
equipment purchases, development costs, proprietary knowledge and human
capital invested into them. These non-recurring costs lead to a reluctance of
Theoretical Background
17
incumbents to cannibalize existing technologies for new technology developments
(Kamien & Schwartz, 1982).
• Political influence: Because of a relative low commercial drive for space exploration,
the space sector, especially the scientific domain, remains highly funded and
controlled by governmental entities. This makes technology investment decisions
highly subject to policy changes caused (in part) by political changeovers.
2.3.3 Space Technology Development
The space sector has always been regarded as a high-tech sector that boosts science in a
range of scientific fields such as meteorology, astronomy, geography, geodesy and
medicine. Due to research & development efforts and the therefrom resulting innovations,
the technological capabilities of the space sector are steadily increasing. Because of
budget constraints, however, only a small portion of the inventions and technology
concepts available can be researched and eventually developed. These technology
concepts are mostly incremental innovations upon the dominant technology and provide
small improvements in the performance of a technology. According to Summerer (2009)
this is partly caused by a risk-adverse culture in the space sector that leaves only a small
margin of freedom for testing innovations in subsystems that are not imperative for
achieving mission success.
Incremental innovations are the opposite of radical innovations (Henderson & Clark,
1990). Radical or breakthrough innovations are innovations that cause a technology
domain to make a leap in its performance evolution (Veryzer, 1998). Radical innovations
are considered as totally new technologies within a technology domain because of their
fundamental differences compared to the previous dominant technology. To further clarify
this, Leifer et al. (2000) describe an incremental innovation as the exploitation of a
technology while a radical innovation is the exploration of a new technology. In general,
radical innovations have the potential to be more beneficial to the space sector than
incremental innovations.
In the space sector, technology development can come from a technology push or
through a demand pull. Technology push means, that a technology is developed and
produced before an actual need for it arises while a demand (or market) pull is
characterized by the identification of a need for a specific technology and the subsequent
development of it (Martin, 1994). When looking at the technology push and demand pull
models and drawing a parallel to technology development in the space sector, basic
research can be identified as the technology push factor while technology developed for
specific missions can be identified as the demand pull (Summerer, 2011). When looking
Theoretical Background
18
for disruptive technologies, technology push areas are of particular interest because it is
them that mostly result in breakthrough technologies while pull investments result more in
incremental innovations (Nemet, 2009; Carayannis & Roy, 2000).
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DLR Study Findings 3
This chapter describes the findings and the steps of the method development process
already performed by the DLR study Disruptive Technology Search for Space Application.
The outcome of these steps is considered given knowledge for the purpose of this paper
and thus serves as additional theoretical background for the development of the
evaluation method.
Disruptive Space Technologies 3.1
In order to develop an evaluation method for disruptive technologies in the space sector,
the specifics of this sector have to be considered and the theory of disruptive technologies
has to be reviewed in respect to its applicability on space technologies. Section 2.3
elaborated on the space sector infrastructure, requirements that exist specifically for space
technologies and the different pathways of space technology development within this
sector. Through insights gained in this section it has become clear that the space sector is
sufficiently different from terrestrial (mass) markets and that a reassessment of the theory
of DTs and the creation of a new theory on disruptive technologies within the space sector
is necessary.
3.1.1 Disruptive Technologies in the Space Sector
To better understand the impact, evolution and manifestation of disruptive technologies
and the path they take in replacing existing technologies, several technologies that have
been disruptive for the space sector in the past have been investigated.
Although some of the characteristics of DTs are the same in conventional markets as they
are in the space sector (for example they both start developing in a niche market before
encroaching on the market of the dominant technology), a historical analysis of five
technology concepts performed in the study DLR study Disruptive Technology Search for
Space Application has shown a number of important differences between the DT theory
as described by Christensen and the way disruptive technologies disrupt the status quo of
the space sector. The major difference seems to be that with the disruption of
technologies no major shifts were observable in the competitive market layout. This is
most likely caused by a combination of the following factors, which also mark the biggest
differences between technologies in the space sector and technologies in conventional
markets:
• Development time: The development of a space technology takes a long time and
therefore the response time of the incumbents to the new technology is high.
DLR Study Findings
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They can either choose to start a development process of their own (if the
development time permits it) or take over the company marketing the new
technology.
• Risk: The long development time and the high reliability requirements of a space
technology cause the risk of an investment to be very high. This constitutes a large
barrier for new startup companies as it makes finding investors very difficult.
• Initial investments: Space technologies often have a significant amount of
equipment purchases, development costs, proprietary knowledge and human
capital invested into them. These non-recurring costs lead to a reluctance of
incumbents to cannibalize existing technologies for new technology developments.
• Flight heritage: A dominant space technology already has a long flight heritage.
Flight heritage means that the technology has already been extensively tested in
space, which increases reliability and decreases risk. A new space technology
candidate has to be a significant improvement to the dominant technology to
justify the increase in risk and decrease in reliability.
• Market characteristics: The space sector is a complex market that is highly
influenced by governmental entities. Development and usage of a technology is
often linked to political motives and/or social aspects.
3.1.2 Definition of Disruptive Space Technologies
Due to the reasons mentioned in the previous subsection, DTs, as described in business
literature, are not the same in the space sector. Therefore, in the course of this work, an
adjusted theory is developed for the space sector called: disruptive space technologies
(DSTs). When analyzing the innovation literature and the theory of DTs, a resemblance can
be found between radical innovations and DTs. Both are exploitations of new technologies
and replace dominant technologies. Additionally, they both offer a higher performance in
the perceived performance mix. The key difference between radical innovations and
disruptive space technologies is that DSTs do this in an unexpected way. In other words:
they over-perform the dominant technology on an alternate (changed) perceived
performance mix. The key characteristics of DSTs can be summarized as follows:
• DSTs are explorations of new technologies. They represent a significant
improvement in performance along a discontinued perceived performance mix (of
a part) of the market. Therefore, a technology replacement by a DST can be
characterized as an unexpected event in the space sector.
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21
• In the space sector, a technology can still be disruptive even if it does not disrupt
the competitive market layout by pushing the dominant technology
producers/marketers out of the market. A technology replacement in an
unexpected manner can be enough to label a space technology as disruptive. This
means that DSTs focus on the disruption of technologies rather than the
disruption of markets. However, disruption is also caused by market factors
(perceived performance mix) and not solely by technological factors (performance).
• DSTs are product innovations according to the 4P paradigm (product, process,
paradigm and position innovation) of Francis and Bessant (2005). Although a
technology can be either a product or a process (as defined in Subsection 2.1.1)
this research and the theory of DSTs only focuses on product innovations.
From the above mentioned the following definition of DSTs is derived:
A disruptive space technology is an emerging technology that disrupts the status quo of
the space sector by replacing the dominant technology and marking a radical
improvement in the perceived performance mix.
A brief note on the terminology:
Soon after the emergence of the term disruptive technologies, Christensen revised it to
disruptive innovations. This was done for two reasons. For one, innovation is a broader
term and includes paradigm and position innovation (see Subsection 0), in
contradistinction to the term technology, which is usually a product or process innovation.
The other reason was that a technology itself is never disruptive, only its successful
application is. As already argued in Subsection 0, the successful application of a new
technology is defined as innovation thus making the term ‘disruptive innovation’ in
general far more accurate (Christensen & Raynor, 2003). Since, however, the focus of this
research is solely on product innovation it is felt, that the term disruptive space technology
better reflects the subject of this research and is hence deliberately chosen.
Evaluation Method Analysis 3.2
This section presents the summary of an in-detail analysis of the evaluation methods with
respect to the space sector as presented in the “Five Views of the Future” framework by
Vanston and Vanston (2004). The detailed presentation of the analysis would go beyond
the scope of this research and thus, only the results are shown here. In the following, the
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different categories of the framework are depicted, their methods mentioned and
examined on DST relevance.
3.2.1 Extrapolating Methods
Extrapolating methods are based on the view that the future will be a logical extension of
the past. Complex forces will drive the future in a predictable manner and that can be
used for creating forecasts. Based on analyzing trends of the past, forecasts can be made
by extrapolating past data according to mathematical principles (Vanston & Vanston,
2004). The methods that follow this hard view on systems are highly quantitative in
nature. They are: Technology Trend Analysis (Wilson, 1987), Fisher-Pry Analysis (Fisher &
Pry, 1971), Gompertz Analysis (Vanston & Vanston, 1996), Growth Limit Analysis
(Martino, 1993) and Learning Curves (Porter, Roper, Mason, Rossini, & Banks, 1991).
Extrapolating methods cannot be used for forecasting DSTs because DSTs do not compete
with dominant technologies on their primary performance dimension. This makes the
extrapolation of a trend of the past in the performance of the primary performance
dimension useless because one characteristic of DSTs is that they will not follow this trend.
Additionally, for extrapolation, a forecaster would need many accurate data points over a
relatively long period of time in order to extrapolate the trend. Such long periods are
usually not available in the space sector due to the irregular use of space technologies.
That makes identifying trends very complicated and rarely accurate.
3.2.2 Pattern Analysis
Pattern analysts believe that the future will reproduce a replication of past events. This
view of reality has led to a method of identifying and analyzing analogous situations of
the subject technology and applying the found patterns to predict its future development
(Vanston, 2003). The adoption of color television, for example, closely followed that of
black-and-white television and that, in turn, followed the pattern of radio adoption. Thus,
one might reasonably forecast the pattern for future adoption of high-definition television
by examining the pattern of past adoption of color television. However, it is quite possible
to choose an invalid analogy and, in any case, future developments never exactly replicate
past analogies. This field differentiates itself from extrapolators in a way that it is broader
by focusing on more than one single performance dimension or technology replacement.
Pattern Analysis methods are: Analogy Analysis (Porter et al., 1991), Precursor Trend
Analysis (Martino, 1993), Morphological Matrices (Bright, 1978) and Feedback Models
(Bright, 1978).
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Pattern Analysis is in some degree applicable for forecasting DSTs. Especially Precursor
Analysis can be applied in determining the timeframe of the dominant technology’s
disruption by the DST. This might, however, be difficult to determine due to the low
frequency in which space technologies are used and the inaccuracy of past data (same
reason Analogy Analysis is not applicable).
3.2.3 Goal Analysis
Goal analysts believe that the future will be defined by the beliefs and actions of various
individuals, organizations and institutions. The future is therefore not determined and is
susceptible to alteration by one or several of these entities. Because of this, a forecast can
be made using the stated and implied goals of the various decision makers and
trendsetters (Vanston, 2003). In the case of space industry, a good example would be the
European space policy and the included technology objectives, which serve as a strategy
for the technology development in Europe. Examples of goal analysts are: Impact Analysis
(Vanston, 1988), Content Analysis (Kroppendorf, 1981), Stakeholder Analysis (Stevensen,
1998) and Patent Analysis (Porter et al., 1991).
In general, Goal Analysis is well applicable for forecasting DSTs because it analyzes
markets instead of focusing on the technology. Impact Analysis has little predictive value
as it merely describes the impact of an innovation if it were to be successful and is
therefore unusable. Content Analysis can be very helpful in the future as this technique
develops but is not useable yet because it cannot follow trends of specific technologies.
Stakeholder Analysis is usable as the stakeholders for technology development in the
European space sector are both pushers and pullers. This, however, can be more of a tool
that helps with the development rather than for the evaluation of a technology. Patent
Analysis examines the number and type of patents approved or rejected over a specific
period of time. It is not a strong indicator for DSTs as they are mostly unexpected by the
main market and therefore the patents involving a potential DST will be non-distinctive
and in very small numbers.
3.2.4 Counter-Punching
Counter-punchers believe that forces shaping the future are highly complex and therefore
future events are essentially unpredictable. They propose that the best way of handling
the future is by identifying a wide range of possible trends and events by monitoring
changes in technical and market environments. The way to cope with changes from an
unpredictable future is by maintaining a high degree of flexibility in the technology
planning process (Vanston & Vanston, 2004). The techniques and methods are: Scanning,
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Monitoring and Tracking (Vanston, 1988; Bright, 1978), Alternate Scenarios (Vanston,
1988; Bright, 1978) and Decision Analysis (Porter et al., 1991). Decision Analysis includes
the Analytic Hierarchy Process (Saaty, 1980) and Concept Scoring (Ulrich & Eppinger,
2000).
In general, Counter-Punching techniques are well applicable for forecasting DSTs.
Especially Decision Analysis techniques are very promising. The Analytic Hierarchy Process
(AHP) can be used for multi-criteria analysis since it involves the reduction of complex
decision such as the ones that have to be made for the evaluation of potential DSTs. The
Concept Scoring method can be used to provide a scoring matrix for ratings on different
criteria weighted accordingly.
3.2.5 Intuitive Methods
Intuitors believe that the future will be realized through a complex mixture of trends,
random occurrences and the actions of individuals and institutions. Because of this
complexity, they believe that no technique can provide an accurate forecast of the future.
Therefore, they usually rely on the subconscious information processing capability of the
human brain and use this to provide useful insights about the future (Vanston & Vanston,
2004). They do this by feeding the brain with information and allow intuition and
experience (tacit knowledge) of experts to make judgments on the likelihood of a future
event. Methods are: The Delphi method (Linstone & Turoff, 1975), Nominal Group
Conferencing (Vanston, 1988) and Structured and Unstructured interviews (Vanston,
1988).
Intuitive methods are very well applicable for forecasting DSTs. Especially the Delphi
technique is ideal for this since it involves a group of experts that has to reach a consensus
on a question. Additionally, the Delphi method benefits from decreased bias through
anonymity and allows communication over long distances. The later makes the Delphi
technique very interesting for the space sector as experts are often located all over the
world. This also makes Nominal Group Conferencing and the interview techniques less
appealing as traveling for interviews might be highly time-consuming and costly.
3.2.6 Conclusions
Table 2 offers an overview of the evaluation methods discussed with the required
information input, type of forecast, applicability for forecasting DSTs and required effort.
As can be seen, the Scanning Monitoring and Tracking techniques (SMTs), Concept
Scoring, the AHP and the Delphi method are ranked highest in their applicability to DSTs
and seem to be most promising.
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25
Table 2
Evaluation methods overview
Method Information input Type of forecast Applicability to DST *
Effort **
Extrapolating Methods
Technology Trend Analysis Performance data Technology performance trend 2 3
Fisher-Pry Analysis Adoption data S-Curve graph 2 4 Gompertz Analysis Adoption data S-Curve graph 2 4
Growth Limit Analysis Performance data S-Curve graph 2 3
Learning Curve Cost data/performance data Cost graph 3 3
Pattern Analysis Analogy Analysis Technology analogy data Adoption pattern 2 2
Precursor Trend Analysis Adoption times Adoption time 2 2 Feedback Models Environment factors Relationship factors 1 2
Goal Analysis Impact Analysis Brainstorm session Unforeseen events 2 3
Content Analysis Trends in media attention Future interest 3 5 Stakeholder Analysis Stakeholder information Influence by stakeholders 3 4
Patent Analysis Patent trends Future scientific interest 3 3 Counter-Punching
Scanning, Monitoring and Tracking techniques
Past and real-time performance data Continuous forecast 5 1
Alternate Scenarios Various sources Scenarios Forecast 2 2 Analytic Hierarchy Process Expert opinions AHP model 5 2
Concept Scoring Expert opinions Potential rating 4 4 Intuitive Methods
Delphi method Expert opinions Expert ratings 5 2 Nominal Group Conferencing
Expert opinions in brainstorming form Expert ratings 3 2
Structured and Unstructured interviews Interviews Expert ratings 3 3
* 1=Not applicable, 2=Somewhat applicable, 3=Reasonably applicable, 4=Well applicable, 5=Very well applicable ** 1=Heavy, 2=Substantial, 3=Reasonable, 4=Little, 5=Very little
Search Strategy Development 3.3
In order to explore the different technology concepts available and to create a database of
potential DST candidates that will serve as a source for the DST evaluation method, a
broad technology scan is performed. The first step of this technology scan is the
development of the search strategy where a suitable concept for identifying DST
candidates is devised. Since the development and application of the search strategy is not
object of this study, the process is only summarized and not elaborated on in detail. The
created database is used as a source of data in in the case study presented in Chapter 6.
In order to form a search strategy, a viable search method is selected and search criteria
are defined. This is done by analyzing existing search methods with respect to space sector
specifics and hence determining their applicability for a DST candidate search. The search
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26
methods considered here are the following: The Lead User method (von Hippel, 1988), the
Document Influence Model (Gerrish & Blei, 2010), the Quid algorithm (Giles, 2011),
patent search methods (Hunt, Nguyen, & Rodgers, 2007) and survey-based data collection
methods (Franklin & Walker, 2010). Table 3 shows the key features of each method along
with its advantages and disadvantages.
Table 3
Search methods overview
Key Features Advantages Disadvantages
Lead User method Identifies needs of lead users to detect future
technology trends
Can identify technology needs and therefore
opportunities for disruptiveness
Not usable for small markets like the space
market
Document Influence Model
Searches in a collection of articles for texts that
influence the language of following texts
Can detect most influential documents
in a collection
Needs a lot of articles about technologies and detects DST´s too late
The Quid algorithm Uses many different
information sources and its own algorithm
Can detect connections between different
fields and disciplines
The algorithm is not published and it is in the
beta test phase
Patent search methods
Searches in databases of over 70 million patents
Huge up to date database
Lack of a customized search program for DSTs /
very time intensive
Survey-based data collection methods
Can detect spin-in technologies by inquiring
individuals of other markets
Collection ideas from many different
individuals and working fields
Results depend on who is asked / willingness to
participate is often low
Survey-based data collection methods are found to be the most viable for a potential DST
search and thus incorporated into the search strategy in form of an internet-based expert
survey. In order to broaden the scope of the search, the strategy is complemented with a
desk research and a technology database search.
Research Methodology
27
Research Methodology 4
This chapter elaborates on the methodology of the evaluation method design. Section 4.1
describes the process of the evaluation method selection. After the method is chosen the
criteria, which the technologies will be evaluated upon, are selected. A number of
different approaches are examined and the appropriate criteria selected. This is presented
in Section 4.2. The methodology of the subsequent selection of a suitable weighing
method is described in Section 4.3.
Evaluation Method Selection 4.1
The evaluation method is selected on the basis of the evaluation method analysis
presented in Section 3.2. The most applicable methods for DST evaluation (see Table 2)
are examined on their ability to fulfill certain requirements. These requirements are derived
from the general needs of the space sector as presented in the space sector analysis
(compare Section 2.3), the specific needs arising from the theory on disruptive space
technologies and the needs that have become evident during the course of this work.
They are the following:
• Quality and reliability of data: The selected method must be able to produce
reliable data with a high quality to ensure the highest possible precision of the
evaluation process.
• Reliability of method: The selected method must be a well proven method with
little or no doubt about its effectiveness, its reliability to produce accurate results
and its ability to meet the difficulty of evaluating and forecasting future
technology concepts
• Need for a pre-selection: The technology scan already performed has made
evident that the number of technology concepts with innovation potential from
both in- and outside of the space sector is very large. However, the technology
concepts that actually have the potential to be disruptive for the space sector are
far less. The ability to filter out the technology concepts that are too immature, do
not have a sufficient disruptive potential or are outside of the search scope is an
essential element of the method.
• Time allocation/work effort: The selected method must represent an amount of
work effort that does not exceed a certain limit. In order to evaluate existing
technology concepts and have results within a reasonable timeframe, time
allocation and work effort of the method must be such, that it is performable
inside a six to twelve month period.
Research Methodology
28
A combination of methods that fulfill the above-listed requirements to the highest extend
is chosen. The following four methods have scored highest on their applicability for DST
evaluation and are examined on their ability to comply with the requirements.
4.1.1 The Analytic Hierarchy Process
The Analytic Hierarchy Process (AHP) is a method for multi-criteria decision analysis (Saaty,
1980). It involves the reduction of complex decisions to a series of pair-wise comparisons
and then then synthesizing the results. Decision-makers arrive at the best decision with a
clear rationale. Users of the AHP first decompose their decision problem into a hierarchy
of more easily comprehended sub-problems, each of which can be analyzed
independently. Once the hierarchy is built, the decision makers systematically evaluate its
various elements by comparing them to one another. In making the comparisons, the
decision makers can use concrete data about the elements, or they can use their
judgments about the elements' relative meaning and importance. It is the essence of the
AHP that human judgments, and not just the underlying information, can be used in
performing the evaluations. This makes the technique semi-qualitative. An example of the
AHP is shown in Figure 8.
Figure 8. Example of the AHP process. A decision (goal) is split unto sub-decisions (criteria). Each
alternative is evaluated indiviadually on each criterion, which then in turn are combined to form the
goal.
4.1.2 The Delphi Method
The Delphi method is a widely used and accepted technique for achieving convergence of
opinion and gathering data from respondents within their domain of expertise (Hsu &
Sandford, 2007). Its far-reaching field of application includes two particular uses that
represent the main goals of Delphi surveys and their benefits: The first is to provide
Research Methodology
29
judgmental data in areas, where hard data is either unavailable or too costly to obtain and
can be used as input data in studies. The second is the use of the Delphi technique in the
process of supplying decision makers with reliable expert opinions (Helmer, 1975). In
extension, both of these applications are often used as forecasting tools (Rowe & Wright,
1999) or as part of technology forecasting methods.
The Delphi method has its origins in US American defense research. Sponsored by the
United States Air Force and developed by the RAND Corporation in the mid-1950s mainly
by Norman Dalkey and Olaf Helmer (1963), it had the purpose of estimating the effects of
a massive nuclear attack on the United States (Helmer, 1975). Even if all the factors could
have been assessed, which is considered unlikely, a statistical analysis of this scale would
not have been possible with the computers of that time. Thus, taking into account the
opinion of experts was the only feasible solution for a prediction of that kind and
delivered the original justification for the first Delphi study (Linstone & Turoff, 1975).
Since its invention, the Delphi Method has come a long way. While used mainly as a
technology forecasting tool in the mid-1960s (Helmer, 1975), it has evolved to arguably
one of the most popular incentive evaluation methods today with the number of studies
being conducted rising in only a decade from a three digit count in the late 1960s to a
four digit number in the 1970s (Linstone & Turoff, 1975). Since then, the field of
application has been extensively diversified and its characteristics have been expanded in
practice and in literature (Häder & Häder, 1998).
A general description of the Delphi method given by Wechsler (1978) reads as follows:
It is a survey which is steered by a monitor group, comprises several rounds of a group
of experts, who are anonymous among each other and for whose subjective-intuitive
prognoses a consensus is aimed at. After each survey round, a standard feedback
about the statistical group judgment calculated from median and quartiles of single
prognoses is given and if possible, the arguments and counterarguments of the
extreme answers are fed back. (pp. 23f.)
According to Linstone and Turoff (1975), there are two basic forms of the Delphi process.
The first is the “paper-and-pencil version” where a small monitor team develops a
questionnaire, which is then sent to the participants of the survey. Upon return of the
questionnaire, a new questionnaire is created based on the answers on the original one.
The next iteration round informs the participants of the results of the first round and gives
them the opportunity to re-evaluate their opinions taking into consideration the
knowledge of the entire group. This form is called the “conventional Delphi”.
Research Methodology
30
The second form called “Delphi conference” replaces the monitor team with a computer
programmed to carry out the compilation of the group results. This approach has the
advantage that the delay between the iteration rounds is eliminated and the process is
concluded much faster. It requires however, that the characteristics of the communication
are well defined before the Delphi is undertaken since they cannot be later adjusted
according to the group responses (Linstone & Turoff, 1975).
One of the main advantages of the Delphi method is that it constitutes a process of
gaining consensus from a group of experts while maintaining their anonymity to decrease
bias. According to Dalkey (1969), bias can come from communication that occurs in a
group process and that deals with individual interests rather than focusing on solving the
problem. Furthermore, it can come from the effect that dominant individuals have over
others in terms of opinion forming. Without the presence of others, respondents can
revise their answers without having to fear social implications. Another advantage of this
method is the low cost in comparison to a high output. This is well illustrated by Jillson
(1975) in the example of a policy Delphi on drug abuse, a special form of the Delphi
method (see Turoff, 1970). The ability to conduct a Delphi with respondents spread over a
wide geographic area is another advantage of the Delphi method (Linstone & Turoff,
1975).
Time requirements can be seen as one of the biggest drawbacks of the Delphi method.
The conclusion of each iteration round can only be conducted once all the participants
have sent in their answers. As a consequence of this delay, participants can lose interest
and drop out the study. Lindstone and Turoff (1975) regard the following as the most
common reasons for a Delphi failure:
• Imposing monitor views and preconceptions of a problem upon the respondent
group
• Assuming that Delphi can be a surrogate for all other human communications
• Poor techniques of summarizing and presenting the group response
• Ignoring and not exploring disagreements
• Underestimating the demanding nature of a Delphi and the fact that respondents
should he recognized as consultants and properly compensated for their time
The field of application for the Delphi method is vast. As previously stated, the Delphi
method can be applied to virtually any circumstance and endeavor where data is not
accurately known or available. A few of them, developed as early as 1975 are given
exemplarily (Linstone & Turoff):
• Gathering current and historical data not accurately known or available
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31
• Examining the significance of historical events
• Evaluating possible budget allocations
• Exploring urban and regional planning options
• Planning university campus and curriculum development
• Putting together the structure of a model
• Delineating the pros and cons associated with potential policy options
• Developing causal relationships in complex economic or social phenomena
• Distinguishing and clarifying real and perceived human motivations
• Exposing priorities of personal values, social goals
Fundamental criticism as to whether or not the Delphi principle works cannot be found in
modern literature any more. The virtually proven reliability of the method and the vast
number of applications it has successfully undertaken can be seen as probable reasons for
that (Häder & Häder, 1998). It is, however, the massive criticism that the Delphi method
has undergone since its invention that allows it to be the dependable and consistent
evaluation tool as we know it today. Ranging from skepticism to total rejection, the
criticism of the method has evoked a bulk of methodical research and controversy in
literature that has influenced the method in a positive way (Häder & Häder, 1998).
4.1.3 Concept Scoring
The concept scoring matrix incorporates a ranking of concepts through a structured
method (Ulrich & Eppinger, 2000). It involves the selection of a concept for investment by
taking the following steps:
1. Prepare a selection matrix
2. Rate concepts
3. Rank concepts
4. Combine and improve concepts
5. Select one or more concepts
6. Reflect on the results of the process
An example of the matrix used in this method is illustrated in Table 4. It shows a scoring
of different concepts. Each concept is scored on three different criteria that are again
divided into sub-criteria. The method uses a weighted factor to adjust the level importance
of each criterion and sub-criterion. The allocation of the weighted factor per criterion
differs with every evaluated concept and has to be determined by the evaluator. Most
criteria result in numbers that can be compared with each other.
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Table 4
Example of a concept scoring matrix
4.1.4 Scanning Monitoring and Tracking Techniques
Scanning, Monitoring and Tracking techniques are based on the principle that for most
new technologies a considerable amount of time is required from invention to innovation.
When considering this, an alert organization can take advantages of this lag-time through
the techniques discussed before. While all techniques involve the analysis of technology
development within a sector, they do differ in purpose, methodology, and degree of
focus.
Scanning techniques involve a broad scan of a sector in order to detect promising
technologies and different trends. Monitoring follows the trend in broad fields and
markets. Finally, tracking involves the continuous observation of developments in a
specified area (specific technologies, market developments etc.). Results of these
techniques can be highly quantitative to basically qualitative, depending on the technique
used. These techniques require a high amount of effort over a continuous period but
provide a real-time protection against disruptive effects within a market.
Criteria Selection 4.2
After selecting a combination of methods that are applicable for evaluating space
technologies and fulfill the listed requirements, the different criteria, on which the
technologies will be evaluated upon, are determined. Criteria are different factors that
determine the overall value of a technology. Business management literature has already
spawned several journal papers and books on evaluating, forecasting and predicting
Wheighted Wheighted Wheighted WheightedRating Score Rating Score Rating Score Rating Score
CRITERION A 25%Sub-criterion A1 5% 7 0,35 10 0,5 8 0,4 7 0,35Sub-criterion A2 20% 4 0,8 5 1 9 1,8 4 0,8
CRITERION B 65%Sub-criterion B1 30% 3 0,9 6 1,8 7 2,1 3 0,9Sub-criterion B2 15% 4 0,6 6 0,9 4 0,6 9 1,35Sub-criterion B3 20% 7 1,4 5 1 5 1 4 0,8
CRITERION C 10%Sub-criterion C1 5% 8 0,4 1 0,05 8 0,4 8 0,4Sub-criterion C2 5% 3 0,15 8 0,4 6 0,3 4 0,2
4,6 5,65 6,6 4,8Total ScoreRank
Criteria Wheight
CONCEPT 1 CONCEPT 2 CONCEPT 3 CONCEPT 4
4th 2nd 1st 3rd
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disruptive technologies. These sources are analyzed in order to determine if their view on
DTs fits with the theory of DSTs, what their evaluation methodology is and if the
methodology can be applied for the evaluation of DST candidates. The different research
groups and their DT prediction methods that are reviewed are:
• Seeing What’s Next methodology (Christensen, Anthony, & Roth, 2004)
• SAILS methodology (Vojak & Chambers, 2004)
• Linear Reservation Space methodology (Schmidt & Druehl, 2008)
• Value Trajectory methodology (Adner, 2002)
• Scenario Planning methodology (Drew, 2006)
• Measuring Disruptiveness methodology (Govindarajan & Kopalle, 2005)
• Propositional Framework methodology (Sainio & Puumalainen, 2007)
From these sources, criteria that seem applicable for the evaluation of DSTs are derived.
The specifics of the space sector as described in Section 2.3 as well as the theory on
disruptive space technologies are taken into account. The different criteria are then sorted
into the four categories of the macro-environmental domains of the STEP analysis. STEP is
an acronym that stands for Social, Technical, Economic and Political and is also sometimes
referred to as PEST or SEPT (Peng & Nunes, 2007). It defines the four factors that influence
the business environment and are of importance in decision making and in the creation of
a business strategy (Fahey & Narayanan, 1986). Here, the STEP analysis serves as a
framework for the categorization of the criteria:
• Social: The factors within the social domain influence technology diffusion within
the space sector by influencing the demand of the technology. This means that if
the public perception of a technology changes, the investment decision makers
will be influenced in their technology development decision. The social domain is
fairly weak compared to the other domains but might nonetheless provide an
indicator to disruptiveness.
• Technical: The technical domain measures factors like performance and impacts on
other systems. It is the most important evaluation segment because the over-
performance of a technology is essential to disruption. However, it is important to
note, that the technology does not need to be obviously better than the state-of-
the-art as this would merely identify a sustaining innovation. Over-performance is
rather to be understood as the performance that a group of customers of the
technology finds more suited to its needs than the performance of the state-of-
the-art technology. The performance of a technology in the technical domain is
Research Methodology
34
determined solely by its performance on technical attributes such as efficiency,
reliability, lifetime, mass etc.
• Economic: The economic factor measures the monetary aspects of space
technologies. DSTs are technologies that make operations simpler, cheaper, more
flexible, and/or more responsive compared to the dominant technology. Economic
aspects are of high importance in identifying space technologies. A rating on
economic factors should encompass whether or not the technology concept
provides significant economic benefits to its users.
• Political: In the space sector analysis it is concluded that technology development is
highly influenced by governments and thus by political decisions. Because of this,
the political domain has a fairly strong influence on the development of
technologies.
Criteria Weighting and Scoring 4.3
As already made evident in the description of the domains above, not every domain can
be treated equally regarding the importance of it and its influence on the evaluation
result. It is also reasonable to assume that the different criteria inside the respective
domains have an unequal importance in respect to their contribution to the overall
evaluation of a technology. Therefore, a weighting method is introduced in order to place
the correct value of importance on each domain and on each criterion. Since the Analytic
Hierarchy Process involves the creating of sub-problems and has, furthermore, already
been identified as a valid method for evaluating DSTs, it is used to determine the
importance of the different domains. This is done by following a method called pairwise
comparison. These comparisons are transformed into so called priorities, i.e. weight
factors that are used for the calculation of the weighted score for each technology. The
factors are also checked on their consistency (Teknomo, 2006). The process is explained
below on the example of the 4 domains of the STEP framework.
As a first step, the criteria are compared inside a priority matrix to receive relative weights
to each other, but only in pairs. The values that are used in the priority matrix can be seen
in Table 5. These values apply on all pairwise comparisons done in the course of this work.
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Table 5
The fundamental scale for pairwise comparisons
With these values a comparison matrix is set up, which is then used to calculate the
priorities (i.e. the actual weights) of the AHP process.
Table 6
Pairwise comparison of the AHP criteria for the 4 domains of the STEP framework
Social 1 Technical 9 Technical factors are much more important than social factors because they determine if a DST is better than the state of the art. Weight: 9
Social 1 Economic 5
Economic factors are more important than social factors because a decrease in any form of costs makes the technology more interesting for development. Weight: 5
Social 1 Political 4 Since political factors are highly important within the space sector, it has a moderate increased performance over social factors. Weight: 4
Technical 4 Economic 1 Technical factors are more important than economic factors because a DST might also be a high-end encroachment. Weight: 4
Technical 6 Political 1 Technical factors are strongly more important than political factors because they determine the value of a technology. Weight: 6
Economic 3 Political 1 Economic factors are slightly more important than political factors because an important factor for political decisions are economic factors Weight: 3
Table 6 shows the comparisons and the respective scores, the comparison matrix is
depicted in Table 7.
Table 7
Comparison matrix for priority calculations
Technical Political Economic Social
Technical 1 6 4 9 Political 1/6 1 1/3 4 Economic 1/4 3 1 5 Social 1/9 1/4 1/5 1
Intensity of Importance Definition Explanation
1 Equal importance Two elements contribute equally to the objective
3 Moderate importance Experience and judgment moderately favor one element over another
5 Strong importance Experience and judgment strongly favor one element over another
7 Very strong importance One element is favored very strongly over another, its dominance is demonstrated in practice
9 Extreme importance The evidence favoring one element over another is of the highest possible order of affirmation
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The priorities for the individual criteria are then calculated via the eigenvalues and
eigenvectors. They are the components of the normalized eigenvector of the priorities
matrix:
�𝐀x − 𝜆𝐄� = 0,
where A denotes the priorities matrix, E the unity matrix and x the solution vector,
whereas λ signifies the eigenvalue. With the above given matrix, the equation becomes:
�
1 − λ1/61/41/9
61 − λ
31/4
41/3
1 − λ1/5
945
1 − λ� = 0
From this, the characteristic polynomial is formulated and the solutions 𝜆 are determined
as eigenvalues.
As the values for each criterion are selected more or less arbitrarily on the evaluators’
discretion, the result needs to be checked on its consistency. This is achieved by a
comparison with a random matrix, i.e. a Random Consistency Index (RI) (Teknomo, 2006).
For this, a consistency index CI for the given matrix is calculated via the formula:
𝐶𝐼 = 𝑘−𝑛𝑛−1
,
where n is the number of dimensions of the comparison matrix and k the eigenvalue.
For the scoring of the criteria, different scales such as a ration scale of zero to ten, the
Likert scale (Lehmann, Gupta, & Steckel, 1998), the Guttman scale (Gorden, 1977) and
the phrase completion scale (Hodge & Gillespie, 2007) are examined as to their
applicability to the evaluation method.
Presentation of the DST Evaluation Method
37
Presentation of the DST Evaluation Method 5
This chapter presents the evaluation method that is used to identify the technology
concept with the highest potential for disruptiveness in the space sector. It consists out of
a three step process that involves a combination of the Analytic Hierarchy Process, the
Delphi method and Concept Scoring.
A prerequisite for the application of the DST evaluation method is the existence of a
technology concept database, which can be used as a source for evaluation. The creation
of such a database, however, is not part of this work. The methodology on the creation of
a search strategy that can be used to create such a database is briefly elaborated on in
Section 3.3.
DST Evaluation Method 5.1
The DST evaluation method is a process that consists out of a series of steps that each
involve the evaluation and selection of a certain number of technology concepts. The
ultimate goal of the method is to rate and eventually select the technology concept with
the highest potential for disruptiveness out of the initial number of available concepts. In
order to accomplish this, a combination of three different technology evaluation methods
is applied. In each step of the process, a ranking is made and only the top n technology
concepts are forwarded to the next step (with n being a number depending on the
current step).
The level of work effort and evaluation preciseness increases progressively. With each
step, the methods applied for the evaluation of the remaining technology concepts
become more elaborate. This ensures that the highest possible evaluation accuracy and
result quality are maintained while limiting work effort and time requirements. The three
steps of this process and their respective methods are explained below.
The first step is called pre-filtering. In this step, the technology concepts is filtered in order
to single out technology concepts that are too immature, do not have a sufficient
disruptive potential or are outside of the search scope. Especially technology concepts
where the available information is very limited or indistinct cannot be evaluated
adequately by the following procedures and need to be filtered out. This step needs to be
a part of the evaluation method and not part of the search strategy so that the technology
scan can be performed without bias and according to the search rules defined by the
strategy. The pre-filtering is done by the members of the DST project team. The goal of
this step is to narrow down the database to not more than 200 technology concepts.
Presentation of the DST Evaluation Method
38
The second step is called AHP pre-selection. The top 200 (or less) technology concepts of
the database, as established by the pre-filtering process, are evaluated by a group of
experts. The Analytic Hierarchy Process is applied to break down the decision of the
experts into four sub-decisions, those being the four categories of the STEP framework.
Each expert is given the list with the technologies, accompanied by a short description of
its main features and its maturity. The technologies are then rated on their performance
on social, technical, economic and political factors. The ratings are inserted into a
simplified concept scoring matrix and the total score of each technology calculated based
on the mean score of the experts’ answers. The experts are a group of 10 people that are
not specialized in one field of work but rather have a broad understanding of all space
technologies. They are familiar with space sector specifics as well as political, social and
economic aspects. They also possess an above average amount of experience that enables
them to roughly assess the potential value of a technology on the basis of the short
description given to them. At the end of this process, the technologies are ranked and
sorted into technology domains such as power, propulsion, materials etc. The goal of this
step is to narrow down the database to 5 technology concepts per technology domain.
The third step is called Delphi method. The top 5 per technology domain technology
concepts of the database are evaluated by a group of experts via a Delphi survey. The
experts are rating the technologies on a number of criteria that correspond to the before
mentioned categories of the STEP framework. These ratings are inserted into a detailed
concept scoring matrix and the total score of each technology calculated based on the
mean score of the experts’ answers. The Delphi experts are a group of 10 people that are
experts within their respective technology domain. They are able to fully assess technology
concepts even with little knowledge about the characteristics of the technology.
Additionally, they are familiar with the market dynamics corresponding to their specific
field of application as well as political and social aspects. The goal of this step is to narrow
down the database to not more than 1 or 2 technology concepts per technology domain.
The above described are guidelines as to how to perform the DST evaluation. Details of
each step are not fully discussed here but left open to be determined during the
application of the method and according to the given situation. An example of the
application is given in Chapter 6.
Criteria Selection 5.2
For step two and step three of the DST evaluation method, different criteria are selected,
on which the technologies are evaluated upon.
Presentation of the DST Evaluation Method
39
As already mentioned in the section above, the evaluation criteria for step two of the
method, the AHP pre-selection, are the four domains of the step framework. Other than
that, no further sub-criteria are selected in order to keep the work effort for the experts of
this step inside a reasonable frame (up to 200 technologies must be read/understood and
evaluated on 4 different aspects).
For step three, the Delphi method, the following criteria are selected and sorted into the
STEP domains.
5.2.1 Social Criteria
Social Question 1 (SQ1): Compare the new technology (technology X) to the existing
dominant technology (state of the art) in respect to environmental benefits.
Environmental aspects have become increasingly important in today society (Dunlap,
1991). Using a technology might lead to advantages or disadvantages to the Earth’s
environment. Society’s opinion on the benefits of space technologies is partially governed
by these benefits or drawbacks. A good example of how an environmental issue
influenced a space program is the launch of Cassini-Huygens. The spacecraft had a
radioisotope thermoelectric generator on board and a major civil movement against it
fearing nuclear contamination in case of a launch failure was formed (Hoffman &
Grossman).
Social Question 2 (SQ2): Are you aware of any ethical dilemmas or social problems
associated with technology X?
Since the beginning of the space era in the 1950’s ethical dilemmas have played a big role
in the formation of space policy. Examples of ethical issues can be found in almost all
manned spaceflight programs where the risk of a failure and the subsequent loss of life
has to be weighed against the benefits of a manned mission. Other examples include the
development of technologies that can be used for military purposes or the use of high
resolution optical devices in satellites with regard to privacy protection. If the usage of the
technology creates any ethical dilemmas, public perception might turn and decrease the
potential for disruptiveness.
5.2.2 Technical Criteria
In the technical domain each technology is evaluated on its six most important
performance attributes in comparison to the existing dominant (state of the art)
technology. The attributes named A1 through A6 are different for each technology and
are determined during the course of the Delphi method by the project team or by the
Presentation of the DST Evaluation Method
40
experts. Examples for performance attributes are efficiency, reliability, lifetime or mass. If a
technology fails to perform under the environmental constraints defined in Sub-section
2.3.2 it is not considered in this process and is filtered out during the pre-filtering phase.
Therefore, attributes such as radiation resistance or vacuum resistance are not considered
as valid attributes for the evaluation in the technical domain.
5.2.3 Economic Criteria
Economic question 1 (EQ1): Compare the new technology (technology X) to the existing
dominant technology (state of the art) in respect to potential for spin-off.
The term spin-off (also sometimes referred to as spin-out) was formed in the context of
space technologies in the 1950’s and describes the usage of technologies or technology
byproducts in commerce and outside of their main field of application (Beer, 2000).
Technologies that have a potential for spin-off have potential for gains beyond their
application as space technology and can therefore profit from favored development
incentive.
Economic question 2 (EQ2): Compare the new technology (technology X) to the existing
dominant technology (state of the art) in respect to production complexity and material
cost.
The development of a technology is linked to its production complexity and material cost.
If either of these two criteria is too high, the gain in performance might not justify the
increase in cost and the technology might not get developed or be used.
Economic question 3 (EQ3): Compare the new technology (technology X) to the existing
dominant technology (state of the art) in respect to operation complexity and
maintenance cost.
High maintenance or operating cost might also have the same results as production
complexity and material cost. A good example for a technology that was discontinued
because of it operation complexity and the therewith associated cost is NASA’s Space
Shuttle Program (Cegłowski, 2005).
Economic question 4 (EQ4): Will the market (area of application) of area of application Y
increase or decrease in the coming years?
A factor determining the success of a technology development is the potential market size
or the number of potential applications of a technology. If this is high, then the
technology development costs can be shared over a wide range of areas. If it is small then
it could be that the technology might be too expensive to develop. Markets and areas of
Presentation of the DST Evaluation Method
41
application can be affected by policy changes, mission types or technology advancements.
For example, plans for colonization of the moon or mars will increase the market and area
of application of life support systems and radiation shielding technologies.
5.2.4 Political Criteria
Political question 1 (PQ1): Do you know or can you think of any restrictions or regulations
that can hinder the entry of technology X into the space sector?
Regulations/restrictions can be laws, directives, technical regulations, existing patterns or
any other kind of restrictions that go against the development or usage of this technology.
Political question 2 (PQ2): In what timeframe do you anticipate this technology to be ready
to be used in a space environment?
If the maturity level of a technology is too low and the expected timeframe for its
development is too large, another technology might advance in the same domain and
take its place before the technology is fully developed. This can decrease the disruptive
potential of a technology. The importance of this question is determined by the scope of
the respective research and the context it is used in.
Political question 3 (PQ3): Are you aware of any political incentive to promote or prevent
the development of technology X (or their field of application)?
Decisions to promote or prevent a technology are often made with regard to political
aspects and not only on the basis of the actual performance of a technology. Political
decisions can be influenced for example by the need to secure employment, the existence
of (trade) agreements, public pressure or be the result of lobby work. Govindarajan and
Kopalle (2005) identified that commitments to existing technologies might limit the use of
the potential disruptive technology. Within the space sector this factor is especially strong
as technologies require an extensive investment in human capital and equipment. This
initial investment and the common resistance to cannibalize existing technology
development is an inhibiting factor against technology development (Kamien & Schwartz,
1982).
Weighing & Scoring 5.3
For the four domain of the STEP framework the pairwise comparison of the AHP process is
performed as elaborated in Section 4.3. The weights for each domain that correspond to
the comparison matrix in Table 7 are:
Presentation of the DST Evaluation Method
42
• Social: 4,5%
• Technical: 61,9%
• Economic: 22,4%
• Political: 11,2%
These weights are used in step two and step three of the DST evaluation method.
The weights for the sub-criteria in the Delphi method are assumed equal because no
incontrovertible comparison can be done among them. Solely the PQ3 is weighted double
the importance of the other two political questions because of the prior mentioned high
importance of governmental influence on space technology development (compare
Section 2.3). The weights are the following: SQ1 50%, SQ2 50%, EQ1 25%, EQ2 25%,
EQ3 25%, EQ4 25%, PQ1 25%, PQ2 25% and PQ3 50%.
The weights of the performance attributes A1 through A6 are different for each
technology and are determined during the course of the Delphi method by the experts.
For the scoring of the criteria in the AHP pre-selection and the performance attributes in
the Delphi method a scale of -5 to +5 is used (modified zero to ten scale) where “–“
indicates that the new technology is worse than the state of the art and “+” that the new
technology is better. Zero means that both the new and the state of the art technologies
perform equally.
For the SEP (social, economic and political) questions a modified quasi-Likert scale is used.
As Jamieson (2004) and others argue, Likert scales fall within the ordinal level of
measurement and using the mean is inappropriate for ordinal data. The SEP question
might, therefore, have a Liker scale like look but the answers are in fact transformed to
the interval scale. The answers differ from case to case and depend on the conditions set
for the respective survey. They have to be devised individually for each application.
Case Study: Disruptive Technology Search for Space Applications
43
Case Study: Disruptive Technology Search for 6
Space Applications
In Chapter 5 the DST evaluation method is described as a generic process applicable to
any dataset of technologies and all domains of the space sector. This chapter presents the
practical application of the method within the frame of a case study. According to Yin
(1993) a case study can be of explanatory, exploratory or descriptive in its design. This
case study can be characterized as both descriptive and exploratory. On the one hand, the
goal is to show the feasibility of the DST evaluation method and familiarize the reader
with the concept and the practical application of the method. On the other hand, this is
the pilot application of the method before its potential application to other cases. The
case study thereby also aims at identifying questions and drawing out implications for
future applications and further research.
Research Objectives 6.1
The application of the DST evaluation method serves two main objectives as depicted in
Figure 9.
Figure 9. Research objectives of the case study.
The first objective is to make a ranking of the 20 currently available technologies that have
the highest potential for disruptiveness inside four major technology domains: materials
and processes, data handling, spacecraft electrical power and propulsion. These four
domains are part of the European Space Agency’s technology tree (European Space
Agency, 2009). This is done on behalf of the European Space Agency who is looking to
invest in the development of potentially disruptive technologies in order to overcome the
merely moderate improvements that the expected evolution of current technologies can
offer.
Case Study: Disruptive Technology Search for Space Applications
44
The second objective is to apply the theoretically developed evaluation method in practice
and thereby show its feasibility and give the proof of concept. Further important aspects
of this objective are the identification of weak spots, the improvement of the method in
future applications as well as the drawing out of implications for future research.
Case Study Design 6.2
In this section the methodology of the application of the DST evaluation method is
described.
6.2.1 Source of Data
The technology scan performed according to the developed search strategy was done in
the context of the DLR study Disruptive Technology Search for Space Application. The
three elements of the search strategy as implemented in the scan are depicted in the
following.
Desk research included exploring news articles, science periodicals, technology journals,
books and internet sources like web pages of companies and research institutes.
The technology database search included the following databases: the Ariadna database
of the European Space Agency’s advanced concept team, the ESA Invitation To Tender
publishing system (EMITS), the ESA Innovation Triangle Initiative (ITI) database and the
NASA External Government Technologies (ETG) data set.
For the expert survey, a database of experts was created by collecting the contact
information of persons in managing and supervising positions in the world’s leading
technology corporations, universities, research institutes and space agencies. The
questionnaire was send to the experts through an internet survey comprised of several
questions focusing mainly on potential DTs in the field of work of the expert and his views
on the future of the space sector. Out of 2,300 individuals contacted around the globe
over 250 responded with 75% of the answers being of sufficient quality for the purposes
of the study. Figure 10 shows the distribution of the respondents according to their field
of expertise.
Through the broad technology scan, a total of over 1,000 technology concepts were
ascertained. They constitute the DST candidate database and are used as a source for the
DST evaluation method.
Case Study: Disruptive Technology Search for Space Applications
45
Figure 10. Distribution of expert survey respondents. Reprinted from Technical Note 3: Broadcast
Scan, Disruptive Technology Search for Space Application (p. 28), by Deutsches Zentrum für Luft-
und Raumfahrt, 2011, Unpublished. Reprinted with permission.
6.2.1 Method Design
The first step is the pre-filtering of the DST candidate database. This process is performed
by the DST project team. Technology concepts that are too immature, do not have a
sufficient disruptive potential or are outside of the search scope are deleted from the
database. Maturity is decided on the basis of the Technology Readiness Level (TRL).
Table 8
The basic technology readiness levels
Technology Readiness Level Level Definition
1 Basic principles observed and reported 2 Technology concept and/or application formulated 3 Analytical & experimental critical function and/or characteristic proof-of-concept 4 Component and/or breadboard validation in laboratory environment 5 Component and/or breadboard validation in relevant environment 6 System/subsystem model or prototype demonstration in a relevant environment 7 System prototype demonstration in a space environment 8 Actual system completed and "Flight qualified" through test and demonstration 9 Actual system "Flight proven" through successful mission operations
Note. Adapted from Technology Readiness Levels Handbook for Space Application (p. 3), by
European Space Agency, 2008, Noordwijk: ESA.
TRL is a scale used by ESA and NASA to describe the maturity of a technology. Table 8
shows the TRL with the corresponding description. Technology concepts with a TRL under
3 or with an expected development timeframe of over 30 years are deleted.
Advanced Materials 9%
Biotechnology 0% Chemistry 2%
Computer Sciences 4%
Electrical and Electronic
Engineering 6%
Information and Communication
Systems 9% Mechanical Engineering 25% Micro- and
Nanoelectronics 8%
Photonics 8%
Physics 6%
Robotics 6%
Misc. 17%
Case Study: Disruptive Technology Search for Space Applications
46
The second step is the AHP pre-selection. It is performed according to the DST evaluation
method guidelines described in Section 5.1. The participating experts of the process are
asked to rate the technologies on each of the four categories of the STEP framework in a
scale of one to ten. A rating under 5 means that the new technology is worse than the
state of the art, rating over 5 that the new technology is better. 5 means that both the
new and the state of the art technologies perform equally. The ratings are inserted into a
simplified concept scoring matrix and the total score of each technology calculated based
on the mean score of the experts’ answers.
The Delphi method is designed as an online questionnaire with three rounds. Häder and
Häder (1998) argue that three round is sufficient for most Delphi surveys. After three
rounds, no new arguments can be expected and the dropout rate increases as the
motivation of the interviewees diminishes.
The SEP questions used in the survey are the same as presented in Section 5.2.
In order to compare the new technology to the dominant technology in the technical
domain, a field of application is established for each technology. The field of application is
defined as the field in which the new technology has the highest potential to overperform
the state of the art techology. The definition of a field of application is done in order to
create a common basis for a comparisson between the new and the old technology.
Before the first round, a number of potentially important performance attributes are
devised for each field of application. They are put together by the DST project team on the
basis of literature research and personal knowledge. These attributes serve as the basis of
the comparison between the state of the art and the DST candidate.
In the first round, the performance attributes are fed to the experts with the request to
select the most important ones or name some of their own. A total of six attributes are
selected or named. This is done for each field of application. The experts are also asked to
answer the SEP questions. The answer options of the SEP questions and the corresponding
values can be seen in Appendix 2 under I. General Notes / Table legends.
In the second round of the Delphi method, the experts are asked to rate the technologies
on the six most important performance attributes that the DST project team selected on
the basis of the answers the experts gave in the first round. The scale uses is the scale of -
5 to +5 as proposed in Section 5.3. They are also asked to rate the importance of each
attribute on a scale of 1 to 5. On this scale they have the liberty to rate each attribute
individually. This method has the advantage that the experts do not have to pay attention
to giving the attributes a total sum of weights of 100%, which would be an unnecessary
Case Study: Disruptive Technology Search for Space Applications
47
challenge considering the number of six attributes. The ratings are transformed to
percentages via the formula shown in Figure 11.
Figure 11. Formula for the calculation of the performance attribute weights.
In the third round of the Delphi method, the experts are given a full record of the answers
of the second round (attribute rating and attribute weight) including a mean score for
each attribute. They are asked to reevaluate their answers and change it towards the
mean if they agree with the assessment of the other experts. This round is performed via
email and each expert is contacted personally.
In both the first and the second round the experts are given the opportunity to comment
on their decisions. This serves the purpose of providing ESA with a better basis for their
final decision making process. It also provides an indication of how substantiated the state
of knowledge of each expert is and how big his motivation is.
6.2.1 Selection of Experts
For the AHP pre-selection process, ten distinguished experts are selected from within the
department of System Analysis Space Segment of the DLR Institute of Space Systems. The
reason for selecting these experts is that the people working in system analysis have a
broad field of expertize as they are involved in work dealing with very diverse fields of
space flight. Another reason for selecting these experts is that the expected compliance
for this considerable amount of work is very high due to the personal relationships of the
administrator of the process with the experts.
For the Delphi method the expert selection is carried out on a global scale. A database of
experts in each of the four technology domains is created. As a start, all participants of the
expert survey of the technology scan (see Sub-section 6.2.1) that expressed interest in the
participation in further studies are contacted. Those who confirmed their participation for
the Delphi method are inserted into the database. In order to expand this database, a
second search for experts is conducted. Persons in managing and supervising positions in
the world’s leading technology corporations, universities, research institutes and space
Case Study: Disruptive Technology Search for Space Applications
48
agencies are contacted and asked for their participation. This second search is done with
focus on those categories that still lack the wanted number of ten experts per category.
Value is also placed on a balanced distribution of experts among different organizations
and different countries in order to reduce bias. A total of 45 experts (at least ten in each
category) are acquired for the Delphi method. A sample of the Delphi expert database is
illustrated in Figure 12.
Figure 12. Sample of the Delphi expert database. Sample shows the diverse composion of the
survey participants regarding age, organization and geographical position. Personal information is
not shown.
6.2.2 Instrumentation and Data Collection
For data collection and evaluation the commercial spreadsheet application Microsoft Excel
is used. The reason for selecting this application is that the initial database for the
technology scan was done on this application and the need for a designated database tool
is nonexistent.
Case Study: Disruptive Technology Search for Space Applications
49
For the Delphi method the online survey tool LimeSurvey is used. LimeSurvey is written in
the general-purpose scripting language PHP. The survey results are exported into Excel
spreadsheets.
The communication with the experts for the AHP pre-selection and the Delphi method is
done via email by the author. The expert surveys are administered by the DST project team
(AHP pre-selection) and the author (Delphi method).
Presentation, Analysis and Interpretation of Results 6.3
In this section, the results of the application of the DST evaluation method is presented,
analyzed and interpreted. In Sub-section 6.3.1 the results of each step of the evaluation
process are presented. The final ranking is analyzed qualitatively and interconnections
between and among the results are established.
6.3.1 Presentation of Results
Through the broad technology scan, a total of over 1,000 technology concepts are
ascertained. The pre-filtering process is applied to the initial database and after this
screening, 220 technologies with a strong potential for disruptiveness remained.
The AHP pre-selection creates a ranking of the 220 technology concepts in the database.
The top ten technologies of each category are shown in Appendix 1. The technologies
selected to go into the Delphi method are not the top 5 technologies of each category like
described in the DST evaluation method. The reason for this is that this being a project
contracted by the ESA, they have the last saying in selecting the technologies for further
evaluation. Their decision is based upon an internal selection process that takes into
account ESA policy, long term intentions and current technology development. The
technologies selected are: three out of the category data, six out of power, five out of
propulsion and five out of materials.
Case Study: Disruptive Technology Search for Space Applications
50
Table 9
Delphi results ranked by category
These 19 technologies go into four different Delphi surveys, one for each category. The
whole Delphi method results in the rankings shown in Table 9 and Table 10.
Table 9 shows the ranking per category and Table 10 shows the total ranking. The colors
are used to better illustrate the positions of the categories in the total ranking. In
Appendix 2, the documentation of the whole survey can be found. Of particular interest
to the interpretation of the results are the comments given by the experts. They provide
further information on the technologies, illuminate the thinking behind the experts voting
and are also a strong indicator for the experts’ motivation and state of knowledge.
Technology Rank by domain Total Score
Metall ic microlattice 1st 1,97Ceramic composite structures 2nd 1,43
Graphite epoxy composites 3rd 1,31 MaterialsNanocrystaline diamond aerogel 4th 1,23
Cathodic arc application of amorp. boron coatings 5th 1,21
Chalcogenide-based reconfigurable memory 1st 1,13Holographic data storage 2nd 0,78 Data
Multicarrier signals 3rd 0,70
Super/ultra capacitors 1st 2,16Sil icon nanowire l ithium ion-battery 2nd 1,65
UltraFlex solar panels 3rd 1,48 PowerAluminium-celmet for l i-ion batteries 4th 1,21
Quantum-dot solar cells 5th 0,52Bacterial nanowire 6th 0,31
Alternative solid propellant CL-20 1st 0,89Micro-electric space propulsion MEP/NanoFET 2nd 0,88
Transpiration cooling 3rd 0,74 PropulsionMagnetoplasmadynamic thruster 4th 0,47
Aerospike engine 5th 0,14
Case Study: Disruptive Technology Search for Space Applications
51
Table 10
Delphi results ranked by total score
6.3.2 Analysis and Interpretation of Results
The total score indicates the performance of the technology in respect to the performance
of the state of the art technology. The scale is a -5 to +5 scale where zero indicates an
equal performance of both technologies.
The total scores show the comparison of the state of the art technology to the DST
candidate. This implies that the technologies are comparable among each other even
cross-domain insofar as the comparison is always done with respect to the state of the art.
A higher score indicates a higher overperformance of DST candidate. As an example,
Super/ultra capacitors offer a performance increase to current technology that is double
the performance increase that alternative solid rocket propellant CL-20 can offer.
When using this data to support decision making in technology development investments
one the following three approaches can be chosen.
When looking to invest in the technologies that have the highest potential for
disruptiveness and offer the highest increase in performance compared to the state of the
art, the total ranking of Table 10 must be considered. In this approach the technology
categories and their interconnections are disregarded and only the raw numbers are
crucial in the decision making process. This approach offers the benefit, that the selected
technologies have the highest potential to be disruptive for their technology categories.
The drawback of this approach is that the importance of the technology category for the
Technology Total rank Total Score
Super/ultra capacitors 1st 2,16Metall ic microlattice 2nd 1,97
Sil icon nanowire l ithium ion-battery 3rd 1,65 MaterialsUltraFlex solar panels 4th 1,48
Ceramic composite structures 5th 1,43Graphite epoxy composites 6th 1,31
Nanocrystaline diamond aerogel 7th 1,23Cathodic arc application of amorp. boron coatings 8th 1,21 Data
Aluminium-celmet for l i-ion batteries 9th 1,21Chalcogenide-based reconfigurable memory 10th 1,13
Alternative solid propellant CL-20 11th 0,89Micro-electric space propulsion MEP/NanoFET 12th 0,88
Holographic data storage 13th 0,78 PowerTranspiration cooling 14th 0,74Multicarrier signals 15th 0,70
Quantum-dot solar cells 16th 0,52Magnetoplasmadynamic thruster 17th 0,47
Bacterial nanowire 18th 0,31 PropulsionAerospike engine 19th 0,14
Case Study: Disruptive Technology Search for Space Applications
52
whole space sector is not taken into account and that the disruption might not take place
on a global scale (or not at all if the importance is very low).
The second approach is to invest in technologies that offer the highest overall benefit to
the space sector. The increase in performance of a technology is put in context with the
importance of its technology category. As an example, a propulsion technology with a
20% performance increase might offer a greater benefit to overall mission capabilities and
cost reduction than a material technology with 60% performance increase. The reason for
this disparity is that the technology categories are located on different system levels.
Propulsion, for example, is considered a bottleneck technology and even small increases in
performance can make a great difference in the overall performance of a space system.
The third approach is a combination of the latter two. From each category the technology
with the highest score is chosen for development. This approach offers the benefit of an
even development in all technology domains and ensures, that in each category, the
technology with the highest potential for disruptiveness is chosen. Drawbacks for this
approach are comparable to the ones of the first approach. The importance of the
technology category is disregarded and a disruption may not occur.
Conclusions
53
Conclusions 7
Limitations of the Study 7.1
One of the biggest limitations of the study results out the theory of DST as formulated in
Section 3.1. This theory focuses solely on product and process innovation and thus,
disruptive space technologies and defined in a way that they exclude paradigm and
position innovation. Especially position innovation, however, can be a major factor when
investigating the disruptive potential of space technologies. The Committee on
Forecasting Future Disruptive Technologies and the National Research Council (2009) have
made categories to determine different kinds of DTs. These categories include:
• Enablers: A technology that makes one or more new technologies, processes or
applications possible.
• Catalysts: A technology that alters the rate of change of a technical development
or alters the rate of improvement of one or more technologies
• Morphers: A technology that when combined with another technology creates a
new technology.
• Multiple technology disruption: A technology that replaces not only one, but
multiple technologies. By its self the technology is not better than a single
technology, but because of its combined function, the technology is better than
the whole of the single technologies.
As can be seen, these categories do not comply with the definition of DSTs in this research
and technologies that match these descriptions cannot be identified via the search and
evaluation methods proposed here. They would, however, fit in the general concept if
position and paradigm innovations, as defined by Francis and Bessant (2005), would be
included in the theory. In order to include position and paradigm innovation and consider
the above formed categories, a completely different approach has to be chosen. The
theory of DST has to be adjusted to encompass the remaining two “P’s” and the search
strategy, expert selection and criteria design has to be geared towards those two
categories.
Further limitations of the study result out of the wide set scope for the identification of
technology concepts. The heterogeneity of these technology concepts, even when sorted
into broad technology domains like power or propulsion, is such, that the experts selected
to evaluate them need to have different field of expertize. They cannot effectively be
experts on all technologies alike. This was made evident by some of the comments of the
experts, who stated during the Delphi survey that they knew only little about a specific
Conclusions
54
technology because it was too specialized. This could be countered by reducing the range
of the considered technology domains and focusing on only one. The formation of
subcategories inside this one domain and the selection of dedicated experts for each
subcategory will very probably increase the results accuracy and the quality of the
evaluation method. It will also increase motivation of the experts to follow through the
evaluation processes as all technologies will be of interest to them.
Another limitation of the study, made evident during the application of the DST evaluation
method, was the time and manpower resources available for the AHP pre-selection step.
Two hundred and twenty technology concepts with four evaluation categories per
concept result in a total of 880 choices the experts had to make. Given the time
requirements and the amount of experts selected for this task, the results can be
described as only a rough assessment of the technology concepts. An allocation of more
experts, a larger timeframe and some additional incentive (e.g. financial compensation)
could increase the accuracy and quality of the results.
Implications for Future Research 7.2
As mentioned above, one goal for future researchers could be to include paradigm and
position innovation in the scope of the DST theory. However, product and position
innovation cannot be evaluated in the same manner. A different approach than the one
utilized for product innovation evaluation needs to be developed for position and yet
another for paradigm innovations. For position innovations, the criteria of the search
strategy need to be adjusted to include technologies that are not new and do not provide
an obvious increase in performance but have the potential to fulfill one or more of the
categories established by the Committee on Forecasting Future Disruptive Technologies.
Also, the mindset of the experts and possibly the selection of them need to be changed.
When looking for position innovation it is important to have people with experience in a
broader sense and an open mind as experts, which will enable them to recognize a
technology with the potential for disruptiveness in this category. Furthermore, the criteria
need to be altered. The focus, especially in the technical domain, has to be more on the
future importance of the criteria and not on their current importance. Finally, the
terminology, particularly the word technology, will have to be revised in order to avoid
confusion with the special case of technology evaluation. Paradigm innovation does not
necessarily involve the introduction of a (new) technology. This needs to be taken into
account when devising an evaluation method for concepts with disruptive potential in the
paradigm category.
Conclusions
55
The dynamics of the space sector provide further implications for future research. The
space sector analysis performed in this study describes the space sector as a quasi-
monopsony market with governmental institutions being the main investors in space
technologies (compare Sub-section 2.3.1). This, however, is changing. Commercial space
exploitation is gaining importance for the space sector in light of ongoing budget cuts and
the privatization of the space sector (Tkatchova, 2011). This change in actors can lead to a
change in innovation dynamics, pathways of technology development and disruption
mechanisms currently in effect.
Important lessons learned from the Delphi method are summarized below:
• The expert selection is the most important element of the Delphi method. Large
discrepancies regarding motivation and knowledge were observed among the
experts. The selection of the right experts guarantees not only a lower dropout
rate but also a much higher quality of answers. A noticeable difference was
observed between experts that were randomly acquired and those that
participated in the study based on recommendations, even if the one
recommending them did not have any liaison to the project team.
• A second selection process of experts based on their performance in the first
round of the Delphi is advisable. During the course of the survey some experts
excelled while others delivered only mediocre results. A reevaluation of the experts
could be done according to the quality of their answers regarding the comments
or/and the time they spend for the completion of the survey.
• An inquiry on the experts’ knowledge on a specific technology is essential. Some
experts may or may not know a great deal about a specific technology. This
assessment has to be made in order to increase or decrease the weight of the
expert’s opinion if necessary.
Recommendations 7.3
As a next step in the evaluation process of the technologies, the roadmapping of the
technologies with the highest potential for disruptiveness is recommended. Technology
roadmapping is a needs-driven technology planning process that helps identify, select, and
develop technology alternatives to satisfy a set of needs (Garcia & Bray, 1997). In this case,
these needs can be defined as the specific conditions needed in order for the technology
development to take place. The roadmap shall most notably contain information on the
necessary development steps a potentially disruptive space technology has to accomplish
before it matures. In this, the roadmap will provide a framework to help plan and
coordinate the technology development.
Conclusions
56
It is also recommended that the results of this study are reevaluated and verified in the
future. To corroborate the disruptive potential of the highest ranked technologies, a
repetition of the evaluation process at least every five years is recommendable in order to
keep up with current developments on a technological and socio-political level. A
repetition of the process will also be an important step in the validation of the DST theory
and will contribute to the refinement of the process.
The implementation of scanning, monitoring and tracking techniques as a parallel task to
the technology evaluation process is also recommended. SMTs were deemed impractical
for the current research, as they require an extensive time investment over a longer period
of time. It would, nonetheless, be advisable for any organization that is looking to
establish an early warning system for disruptive space technologies to implement scanning
monitoring and tracking techniques as they will mitigate the chance of unexpected DSTs
arising. One way this can be done is by building upon the created technology database
and integrating a technology tracking system.
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viii
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Appendix 1
xiv
Appendix 1
AHP Pre-Selection Results
Materials
Data
Technology Name Social Technical Economical Political Total
Ceramic Composite Structures 6,00 7,83 6,50 6,83 7,35
Graphene 5,86 7,86 5,86 6,29 7,15
Metalic Microlattice 5,40 7,80 6,00 6,20 7,11
Graphite Epoxy Composite 5,40 7,80 5,60 5,80 6,98
Boron Nitride Nanotubes 4,20 7,40 6,40 5,60 6,84
Elastic Memory Composite Material 6,00 7,50 4,83 6,00 6,67
Carbon Reinforced Plastics (CFRP) 5,50 7,17 5,17 5,33 6,44
Biomimetic Adhesive Polymers Based on Mussel Adhesive Proteins
5,83 7,00 4,50 6,33 6,32
Electroactive Polymers 5,33 7,00 5,00 5,50 6,31
Basalt Fibers 4,83 6,50 6,50 5,17 6,28
AHP Factors
Technology Name Social Technical Economical Political Total
Quantum computing 7,00 9,00 6,50 7,17 8,15
DNA Computer 5,17 8,17 5,50 5,83 7,18
Holographic Data Storage 5,80 8,00 5,40 6,40 7,14
Quantum Sensor 6,17 7,83 6,00 5,67 7,11
Chalcogenide-Based Reconfigurable Memory Electronics
6,17 7,33 6,50 6,17 6,97
Quantum communication 7,00 7,50 6,00 5,50 6,92
Wireless data handling 5,20 7,20 6,00 6,00 6,71
Noise-Robust Speech Recognition for Speech Computer Control
6,60 7,00 5,40 7,00 6,63
Three-dimensional integrated circuit 5,67 6,83 5,67 5,83 6,41
Gallium Nitride semiconductor technology
5,60 7,60 3,20 5,60 6,30
AHP Factors
Appendix 1
xv
Power
Propulsion
Technology Name Social Technical Economical Political Total
High temperature superconductors 6,29 8,00 5,57 6,43 7,21
UltraFlex solar panels 8,00 6,00 9,00 9,00 7,10
Advanced Stirling Radioisotope Generator (ASRG)
4,29 8,00 5,71 5,57 7,05
Quantum-Dot Solar cell 6,67 6,83 7,17 6,67 6,89
Unitized regenerative fuel cell (URFC) 6,00 7,40 5,60 6,40 6,83
Holographic Planar Concentrator Photovoltaic (PV) Module
6,80 7,60 4,40 7,00 6,78
Aluminum-Celmet for Li-Ion Batteries 5,67 7,33 5,83 5,67 6,74
Silicon Nanowire Lithium-Ion Battery 5,20 7,40 5,40 5,60 6,66
Nano Composite Solar Cell 6,20 6,80 6,40 6,20 6,62
Super/Ultra capacitors 5,33 7,00 6,33 5,17 6,58
AHP Factors
Technology Name Social Technical Economical Political Total
Laser propelled light craft 5,50 8,00 6,17 5,50 7,20
Altitude compensating nozzles 5,20 7,80 5,40 5,80 6,93
Fission Fragment Rocket Engine (FFRE) 4,50 7,83 5,67 5,00 6,89
Alternative Solid Propellants: CL-20 5,20 7,80 4,80 5,80 6,79
Micro Electric Space Propulsion (MEP)/ NanoFET
5,33 7,17 6,17 5,83 6,72
Ambient Plasma Wave Propulsion 5,40 7,00 6,20 5,40 6,57
Magneto-plasmadynamic thruster (MPDT) 5,40 7,40 4,60 5,80 6,51
Magnetic Sails 5,00 7,17 5,50 5,33 6,49
Variable specific impulse magnetoplasmarocket (VASIMR)
5,20 7,20 5,20 5,40 6,46
Electrodynamic Tether 5,17 6,50 6,67 6,17 6,44
AHP Factors
Appendix 2
xvi
Appendix 2
Declaration of Academic Honesty
I hereby declare to have written this diploma thesis on my own. All parts of this paper that
are cited literally or in a rough summary from publications or other secondary material are
recognizable and I have clearly defined them with their respective references.
Berlin, Mail 23, 2012
